.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/training_and_testing/plot_one_model_binary_kfold.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_training_and_testing_plot_one_model_binary_kfold.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_training_and_testing_plot_one_model_binary_kfold.py:


K-Fold Cross-Validation: Binary Classification
======================================================

🚀 In this tutorial, we'll explore binary classification using K-fold cross validation. 
We'll show you how to train a fusion model using K-Fold cross-validation with multimodal tabular data. 
Specifically, we're using the :class:`~.TabularCrossmodalMultiheadAttention` model.

Data:

The data we are using is 500 rows of the MNIST dataset, split into top and bottom halves as our two tabular modalities.
The bottom half's values have been inverted to make the task more difficult.
The prediction label will be whether the number is odd or even.

Key Features:

- 📥 Importing a model based on its path.
- 🧪 Training and testing a model with k-fold cross validation.
- 📈 Plotting the loss curves of each fold.
- 📊 Visualising the results of a single K-Fold model using the :class:`~.ConfusionMatrix` class.

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.. code-block:: Python


    import matplotlib.pyplot as plt
    from tqdm.auto import tqdm
    import os

    from fusilli.data import prepare_fusion_data
    from fusilli.eval import ConfusionMatrix
    from fusilli.train import train_and_save_models

    # sphinx_gallery_thumbnail_number = -1








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1. Import the fusion model 🔍
--------------------------------
We're importing only one model for this example, the :class:`~.TabularCrossmodalMultiheadAttention` model.
Instead of using the :func:`~fusilli.utils.model_chooser.import_chosen_fusion_models` function, we're importing the model directly like with any other library method.

.. GENERATED FROM PYTHON SOURCE LINES 38-44

.. code-block:: Python



    from fusilli.fusionmodels.tabularfusion.crossmodal_att import (
        TabularCrossmodalMultiheadAttention,
    )








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2. Set the training parameters 🎯
-----------------------------------
Now we're configuring our training parameters.

For training and testing, the necessary parameters are:
- Paths to the input data files.
- Paths to the output directories.
- ``prediction_task``: the type of prediction to be performed. This is either ``regression``, ``binary``, or ``classification``.

Some optional parameters are:

- ``kfold``: a boolean of whether to use k-fold cross-validation (True) or not (False). By default, this is set to False.
- ``num_folds``: the number of folds to use. It can't be ``k=1``.
- ``wandb_logging``: a boolean of whether to log the results using Weights and Biases (True) or not (False). Default is False.
- ``test_size``: the proportion of the dataset to include in the test split. Default is 0.2.
- ``batch_size``: the batch size to use for training. Default is 8.
- ``multiclass_dimensions``: the number of classes to use for multiclass classification. Default is None unless ``prediction_task`` is ``multiclass``.
- ``max_epochs``: the maximum number of epochs to train for. Default is 1000.

.. GENERATED FROM PYTHON SOURCE LINES 63-93

.. code-block:: Python


    # Binary task (predicting a binary variable - 0 or 1)
    prediction_task = "binary"

    # Set the batch size
    batch_size = 32

    # Enable k-fold cross-validation with k=5
    kfold = True
    num_folds = 5

    # Setting output directories
    output_paths = {
        "losses": "loss_logs/one_model_binary_kfold",
        "checkpoints": "checkpoints/one_model_binary_kfold",
        "figures": "figures/one_model_binary_kfold",
    }

    # Create the output directories if they don't exist
    for path in output_paths.values():
        os.makedirs(path, exist_ok=True)

    # Clearing the loss logs directory (only for the example notebooks)
    for dir in os.listdir(output_paths["losses"]):
        # remove files
        for file in os.listdir(os.path.join(output_paths["losses"], dir)):
            os.remove(os.path.join(output_paths["losses"], dir, file))
        # remove dir
        os.rmdir(os.path.join(output_paths["losses"], dir))








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3. Specifying input file paths 🔮
--------------------------------
We're using the MNIST dataset for this example, and the CSV files are stored in the ``_static/mnist_data`` directory with the documentation files.

.. GENERATED FROM PYTHON SOURCE LINES 97-104

.. code-block:: Python


    data_paths = {
        "tabular1": "../../_static/mnist_data/mnist1_binary.csv",
        "tabular2": "../../_static/mnist_data/mnist2_binary.csv",
        "image": "",
    }








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4. Training the fusion model 🏁
--------------------------------------
Now we're ready to train our model. We're using the :func:`~fusilli.train.train_and_save_models` function to train our model.

First we need to create a data module using the :func:`~fusilli.data.prepare_fusion_data` function.
This function takes the following parameters:

- ``prediction_task``: the type of prediction to be performed.
- ``fusion_model``: the fusion model to be trained.
- ``data_paths``: the paths to the input data files.
- ``output_paths``: the paths to the output directories.

Then we pass the data module and the fusion model to the :func:`~fusilli.train.train_and_save_models` function.
We're not using checkpointing for this example, so we set ``enable_checkpointing=False``. We're also setting ``show_loss_plot=True`` to plot the loss curves for each fold.

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.. code-block:: Python



    fusion_model = TabularCrossmodalMultiheadAttention

    print("method_name:", fusion_model.method_name)
    print("modality_type:", fusion_model.modality_type)
    print("fusion_type:", fusion_model.fusion_type)

    dm = prepare_fusion_data(prediction_task=prediction_task,
                             fusion_model=fusion_model,
                             data_paths=data_paths,
                             output_paths=output_paths,
                             kfold=kfold,
                             num_folds=num_folds,
                             batch_size=batch_size)

    # train and test
    single_model_list = train_and_save_models(
        data_module=dm,
        fusion_model=fusion_model,
        enable_checkpointing=False,  # False for the example notebooks
        show_loss_plot=True,
    )




.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /auto_examples/training_and_testing/images/sphx_glr_plot_one_model_binary_kfold_001.png
         :alt: Loss Curves for TabularCrossmodalMultiheadAttention_fold_0
         :srcset: /auto_examples/training_and_testing/images/sphx_glr_plot_one_model_binary_kfold_001.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/training_and_testing/images/sphx_glr_plot_one_model_binary_kfold_002.png
         :alt: Loss Curves for TabularCrossmodalMultiheadAttention_fold_1
         :srcset: /auto_examples/training_and_testing/images/sphx_glr_plot_one_model_binary_kfold_002.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/training_and_testing/images/sphx_glr_plot_one_model_binary_kfold_003.png
         :alt: Loss Curves for TabularCrossmodalMultiheadAttention_fold_2
         :srcset: /auto_examples/training_and_testing/images/sphx_glr_plot_one_model_binary_kfold_003.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/training_and_testing/images/sphx_glr_plot_one_model_binary_kfold_004.png
         :alt: Loss Curves for TabularCrossmodalMultiheadAttention_fold_3
         :srcset: /auto_examples/training_and_testing/images/sphx_glr_plot_one_model_binary_kfold_004.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/training_and_testing/images/sphx_glr_plot_one_model_binary_kfold_005.png
         :alt: Loss Curves for TabularCrossmodalMultiheadAttention_fold_4
         :srcset: /auto_examples/training_and_testing/images/sphx_glr_plot_one_model_binary_kfold_005.png
         :class: sphx-glr-multi-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    method_name: Tabular Crossmodal multi-head attention
    modality_type: tabular_tabular
    fusion_type: attention

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    Epoch 3:  23%|██▎       | 3/13 [00:00<00:00, 84.00it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  31%|███       | 4/13 [00:00<00:00, 84.19it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  31%|███       | 4/13 [00:00<00:00, 83.82it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  38%|███▊      | 5/13 [00:00<00:00, 83.66it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  38%|███▊      | 5/13 [00:00<00:00, 83.34it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  46%|████▌     | 6/13 [00:00<00:00, 83.75it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  46%|████▌     | 6/13 [00:00<00:00, 83.49it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  54%|█████▍    | 7/13 [00:00<00:00, 84.04it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  54%|█████▍    | 7/13 [00:00<00:00, 83.83it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  62%|██████▏   | 8/13 [00:00<00:00, 83.11it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  62%|██████▏   | 8/13 [00:00<00:00, 82.91it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  69%|██████▉   | 9/13 [00:00<00:00, 83.11it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  69%|██████▉   | 9/13 [00:00<00:00, 82.95it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  77%|███████▋  | 10/13 [00:00<00:00, 83.21it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  77%|███████▋  | 10/13 [00:00<00:00, 83.07it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  85%|████████▍ | 11/13 [00:00<00:00, 83.40it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  85%|████████▍ | 11/13 [00:00<00:00, 83.27it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  92%|█████████▏| 12/13 [00:00<00:00, 83.36it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3:  92%|█████████▏| 12/13 [00:00<00:00, 83.25it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 83.61it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 83.49it/s, v_num=ld_0, val_loss=0.553, train_loss=0.565]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 76.03it/s, v_num=ld_0, val_loss=0.549, train_loss=0.565]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 75.77it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 3:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]         
    Epoch 4:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:   8%|▊         | 1/13 [00:00<00:00, 82.57it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:   8%|▊         | 1/13 [00:00<00:00, 81.19it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  15%|█▌        | 2/13 [00:00<00:00, 83.77it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  15%|█▌        | 2/13 [00:00<00:00, 83.02it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  23%|██▎       | 3/13 [00:00<00:00, 83.00it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  23%|██▎       | 3/13 [00:00<00:00, 82.51it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  31%|███       | 4/13 [00:00<00:00, 82.15it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  31%|███       | 4/13 [00:00<00:00, 81.72it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  38%|███▊      | 5/13 [00:00<00:00, 82.41it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  38%|███▊      | 5/13 [00:00<00:00, 82.00it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  46%|████▌     | 6/13 [00:00<00:00, 82.44it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  46%|████▌     | 6/13 [00:00<00:00, 82.21it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  54%|█████▍    | 7/13 [00:00<00:00, 82.51it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  54%|█████▍    | 7/13 [00:00<00:00, 82.31it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  62%|██████▏   | 8/13 [00:00<00:00, 82.45it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  62%|██████▏   | 8/13 [00:00<00:00, 82.28it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  69%|██████▉   | 9/13 [00:00<00:00, 82.24it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  69%|██████▉   | 9/13 [00:00<00:00, 82.05it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  77%|███████▋  | 10/13 [00:00<00:00, 82.18it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  77%|███████▋  | 10/13 [00:00<00:00, 82.04it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  85%|████████▍ | 11/13 [00:00<00:00, 82.08it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  85%|████████▍ | 11/13 [00:00<00:00, 81.96it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  92%|█████████▏| 12/13 [00:00<00:00, 81.92it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4:  92%|█████████▏| 12/13 [00:00<00:00, 81.79it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 82.39it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 82.28it/s, v_num=ld_0, val_loss=0.549, train_loss=0.549]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 74.70it/s, v_num=ld_0, val_loss=0.536, train_loss=0.549]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 74.45it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 4:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]         
    Epoch 5:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:   8%|▊         | 1/13 [00:00<00:00, 80.78it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:   8%|▊         | 1/13 [00:00<00:00, 79.46it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  15%|█▌        | 2/13 [00:00<00:00, 83.00it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  15%|█▌        | 2/13 [00:00<00:00, 82.29it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  23%|██▎       | 3/13 [00:00<00:00, 83.65it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  23%|██▎       | 3/13 [00:00<00:00, 83.18it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  31%|███       | 4/13 [00:00<00:00, 83.10it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  31%|███       | 4/13 [00:00<00:00, 82.71it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  38%|███▊      | 5/13 [00:00<00:00, 82.55it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  38%|███▊      | 5/13 [00:00<00:00, 82.27it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  46%|████▌     | 6/13 [00:00<00:00, 81.61it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  46%|████▌     | 6/13 [00:00<00:00, 81.38it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  54%|█████▍    | 7/13 [00:00<00:00, 81.94it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  54%|█████▍    | 7/13 [00:00<00:00, 81.74it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  62%|██████▏   | 8/13 [00:00<00:00, 82.23it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  62%|██████▏   | 8/13 [00:00<00:00, 82.04it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  69%|██████▉   | 9/13 [00:00<00:00, 82.36it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  69%|██████▉   | 9/13 [00:00<00:00, 82.19it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  77%|███████▋  | 10/13 [00:00<00:00, 82.11it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  77%|███████▋  | 10/13 [00:00<00:00, 81.97it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  85%|████████▍ | 11/13 [00:00<00:00, 81.84it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  85%|████████▍ | 11/13 [00:00<00:00, 81.71it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  92%|█████████▏| 12/13 [00:00<00:00, 82.09it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5:  92%|█████████▏| 12/13 [00:00<00:00, 81.96it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 82.43it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 82.32it/s, v_num=ld_0, val_loss=0.536, train_loss=0.538]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 74.98it/s, v_num=ld_0, val_loss=0.535, train_loss=0.538]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 74.71it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 5:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]         
    Epoch 6:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:   8%|▊         | 1/13 [00:00<00:00, 80.45it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:   8%|▊         | 1/13 [00:00<00:00, 79.14it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  15%|█▌        | 2/13 [00:00<00:00, 79.37it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  15%|█▌        | 2/13 [00:00<00:00, 78.67it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  23%|██▎       | 3/13 [00:00<00:00, 80.16it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  23%|██▎       | 3/13 [00:00<00:00, 79.72it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  31%|███       | 4/13 [00:00<00:00, 80.88it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  31%|███       | 4/13 [00:00<00:00, 80.51it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  38%|███▊      | 5/13 [00:00<00:00, 81.08it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  38%|███▊      | 5/13 [00:00<00:00, 80.81it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  46%|████▌     | 6/13 [00:00<00:00, 81.54it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  46%|████▌     | 6/13 [00:00<00:00, 81.29it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  54%|█████▍    | 7/13 [00:00<00:00, 81.49it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  54%|█████▍    | 7/13 [00:00<00:00, 81.28it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  62%|██████▏   | 8/13 [00:00<00:00, 81.78it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  62%|██████▏   | 8/13 [00:00<00:00, 81.61it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  69%|██████▉   | 9/13 [00:00<00:00, 82.15it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  69%|██████▉   | 9/13 [00:00<00:00, 81.98it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  77%|███████▋  | 10/13 [00:00<00:00, 82.41it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  77%|███████▋  | 10/13 [00:00<00:00, 82.27it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  85%|████████▍ | 11/13 [00:00<00:00, 82.61it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  85%|████████▍ | 11/13 [00:00<00:00, 82.48it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  92%|█████████▏| 12/13 [00:00<00:00, 82.32it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6:  92%|█████████▏| 12/13 [00:00<00:00, 82.19it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 82.80it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 82.69it/s, v_num=ld_0, val_loss=0.535, train_loss=0.550]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 75.34it/s, v_num=ld_0, val_loss=0.547, train_loss=0.550]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 75.08it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 6:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]         
    Epoch 7:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:   8%|▊         | 1/13 [00:00<00:00, 85.10it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:   8%|▊         | 1/13 [00:00<00:00, 83.50it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  15%|█▌        | 2/13 [00:00<00:00, 82.95it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  15%|█▌        | 2/13 [00:00<00:00, 82.25it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  23%|██▎       | 3/13 [00:00<00:00, 81.80it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  23%|██▎       | 3/13 [00:00<00:00, 81.23it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  31%|███       | 4/13 [00:00<00:00, 81.62it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  31%|███       | 4/13 [00:00<00:00, 81.28it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  38%|███▊      | 5/13 [00:00<00:00, 82.29it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  38%|███▊      | 5/13 [00:00<00:00, 81.96it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  46%|████▌     | 6/13 [00:00<00:00, 82.54it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  46%|████▌     | 6/13 [00:00<00:00, 82.28it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  54%|█████▍    | 7/13 [00:00<00:00, 82.40it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  54%|█████▍    | 7/13 [00:00<00:00, 82.17it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  62%|██████▏   | 8/13 [00:00<00:00, 81.62it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  62%|██████▏   | 8/13 [00:00<00:00, 81.42it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  69%|██████▉   | 9/13 [00:00<00:00, 81.71it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  69%|██████▉   | 9/13 [00:00<00:00, 81.55it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  77%|███████▋  | 10/13 [00:00<00:00, 81.79it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  77%|███████▋  | 10/13 [00:00<00:00, 81.65it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  85%|████████▍ | 11/13 [00:00<00:00, 81.92it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  85%|████████▍ | 11/13 [00:00<00:00, 81.79it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  92%|█████████▏| 12/13 [00:00<00:00, 81.84it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7:  92%|█████████▏| 12/13 [00:00<00:00, 81.72it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 82.12it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 82.01it/s, v_num=ld_0, val_loss=0.547, train_loss=0.527]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 74.57it/s, v_num=ld_0, val_loss=0.529, train_loss=0.527]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 74.31it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 7:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]         
    Epoch 8:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:   8%|▊         | 1/13 [00:00<00:00, 81.83it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:   8%|▊         | 1/13 [00:00<00:00, 80.34it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  15%|█▌        | 2/13 [00:00<00:00, 81.71it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  15%|█▌        | 2/13 [00:00<00:00, 81.02it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  23%|██▎       | 3/13 [00:00<00:00, 82.09it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  23%|██▎       | 3/13 [00:00<00:00, 81.64it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  31%|███       | 4/13 [00:00<00:00, 81.44it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  31%|███       | 4/13 [00:00<00:00, 81.02it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  38%|███▊      | 5/13 [00:00<00:00, 81.53it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  38%|███▊      | 5/13 [00:00<00:00, 81.25it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  46%|████▌     | 6/13 [00:00<00:00, 81.50it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  46%|████▌     | 6/13 [00:00<00:00, 81.27it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  54%|█████▍    | 7/13 [00:00<00:00, 81.47it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  54%|█████▍    | 7/13 [00:00<00:00, 81.27it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  62%|██████▏   | 8/13 [00:00<00:00, 81.62it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  62%|██████▏   | 8/13 [00:00<00:00, 81.45it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  69%|██████▉   | 9/13 [00:00<00:00, 81.46it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  69%|██████▉   | 9/13 [00:00<00:00, 81.29it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  77%|███████▋  | 10/13 [00:00<00:00, 81.72it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  77%|███████▋  | 10/13 [00:00<00:00, 81.58it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  85%|████████▍ | 11/13 [00:00<00:00, 82.01it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  85%|████████▍ | 11/13 [00:00<00:00, 81.87it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  92%|█████████▏| 12/13 [00:00<00:00, 82.18it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8:  92%|█████████▏| 12/13 [00:00<00:00, 82.07it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 82.69it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 82.57it/s, v_num=ld_0, val_loss=0.529, train_loss=0.551]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 75.24it/s, v_num=ld_0, val_loss=0.545, train_loss=0.551]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 74.97it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 8:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]         
    Epoch 9:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:   8%|▊         | 1/13 [00:00<00:00, 80.33it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:   8%|▊         | 1/13 [00:00<00:00, 79.02it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  15%|█▌        | 2/13 [00:00<00:00, 79.83it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  15%|█▌        | 2/13 [00:00<00:00, 79.12it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  23%|██▎       | 3/13 [00:00<00:00, 81.47it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  23%|██▎       | 3/13 [00:00<00:00, 81.02it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  31%|███       | 4/13 [00:00<00:00, 82.37it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  31%|███       | 4/13 [00:00<00:00, 82.03it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  38%|███▊      | 5/13 [00:00<00:00, 82.84it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  38%|███▊      | 5/13 [00:00<00:00, 82.56it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  46%|████▌     | 6/13 [00:00<00:00, 82.75it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  46%|████▌     | 6/13 [00:00<00:00, 82.49it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  54%|█████▍    | 7/13 [00:00<00:00, 83.24it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  54%|█████▍    | 7/13 [00:00<00:00, 83.02it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  62%|██████▏   | 8/13 [00:00<00:00, 83.12it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  62%|██████▏   | 8/13 [00:00<00:00, 82.94it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  69%|██████▉   | 9/13 [00:00<00:00, 83.22it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  69%|██████▉   | 9/13 [00:00<00:00, 83.04it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  77%|███████▋  | 10/13 [00:00<00:00, 83.45it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  77%|███████▋  | 10/13 [00:00<00:00, 83.31it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  85%|████████▍ | 11/13 [00:00<00:00, 82.90it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  85%|████████▍ | 11/13 [00:00<00:00, 82.76it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  92%|█████████▏| 12/13 [00:00<00:00, 82.89it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9:  92%|█████████▏| 12/13 [00:00<00:00, 82.77it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 83.40it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 83.29it/s, v_num=ld_0, val_loss=0.545, train_loss=0.523]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 75.86it/s, v_num=ld_0, val_loss=0.532, train_loss=0.523]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 75.60it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 9:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]         
    Epoch 10:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:   8%|▊         | 1/13 [00:00<00:00, 83.35it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:   8%|▊         | 1/13 [00:00<00:00, 81.96it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  15%|█▌        | 2/13 [00:00<00:00, 82.53it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  15%|█▌        | 2/13 [00:00<00:00, 81.80it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  23%|██▎       | 3/13 [00:00<00:00, 83.13it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  23%|██▎       | 3/13 [00:00<00:00, 82.66it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  31%|███       | 4/13 [00:00<00:00, 83.51it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  31%|███       | 4/13 [00:00<00:00, 83.15it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  38%|███▊      | 5/13 [00:00<00:00, 83.62it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  38%|███▊      | 5/13 [00:00<00:00, 83.34it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  46%|████▌     | 6/13 [00:00<00:00, 83.95it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  46%|████▌     | 6/13 [00:00<00:00, 83.69it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  54%|█████▍    | 7/13 [00:00<00:00, 83.64it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  54%|█████▍    | 7/13 [00:00<00:00, 83.43it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  62%|██████▏   | 8/13 [00:00<00:00, 83.91it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  62%|██████▏   | 8/13 [00:00<00:00, 83.73it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  69%|██████▉   | 9/13 [00:00<00:00, 83.92it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  69%|██████▉   | 9/13 [00:00<00:00, 83.75it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  77%|███████▋  | 10/13 [00:00<00:00, 84.00it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  77%|███████▋  | 10/13 [00:00<00:00, 83.85it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  85%|████████▍ | 11/13 [00:00<00:00, 84.09it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  85%|████████▍ | 11/13 [00:00<00:00, 83.95it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  92%|█████████▏| 12/13 [00:00<00:00, 83.95it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10:  92%|█████████▏| 12/13 [00:00<00:00, 83.82it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 84.33it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 84.22it/s, v_num=ld_0, val_loss=0.532, train_loss=0.517]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 76.58it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 76.31it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 10:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]         
    Epoch 11:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:   8%|▊         | 1/13 [00:00<00:00, 77.44it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:   8%|▊         | 1/13 [00:00<00:00, 76.20it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  15%|█▌        | 2/13 [00:00<00:00, 80.27it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  15%|█▌        | 2/13 [00:00<00:00, 79.61it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  23%|██▎       | 3/13 [00:00<00:00, 80.39it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  23%|██▎       | 3/13 [00:00<00:00, 79.92it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  31%|███       | 4/13 [00:00<00:00, 81.51it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  31%|███       | 4/13 [00:00<00:00, 81.17it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  38%|███▊      | 5/13 [00:00<00:00, 82.07it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  38%|███▊      | 5/13 [00:00<00:00, 81.79it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  46%|████▌     | 6/13 [00:00<00:00, 81.99it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  46%|████▌     | 6/13 [00:00<00:00, 81.76it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  54%|█████▍    | 7/13 [00:00<00:00, 81.84it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  54%|█████▍    | 7/13 [00:00<00:00, 81.61it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  62%|██████▏   | 8/13 [00:00<00:00, 81.23it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  62%|██████▏   | 8/13 [00:00<00:00, 81.02it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  69%|██████▉   | 9/13 [00:00<00:00, 81.48it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  69%|██████▉   | 9/13 [00:00<00:00, 81.31it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  77%|███████▋  | 10/13 [00:00<00:00, 81.68it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  77%|███████▋  | 10/13 [00:00<00:00, 81.51it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  85%|████████▍ | 11/13 [00:00<00:00, 81.97it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  85%|████████▍ | 11/13 [00:00<00:00, 81.85it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  92%|█████████▏| 12/13 [00:00<00:00, 82.20it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11:  92%|█████████▏| 12/13 [00:00<00:00, 82.08it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 82.49it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 82.36it/s, v_num=ld_0, val_loss=0.531, train_loss=0.517]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 74.80it/s, v_num=ld_0, val_loss=0.537, train_loss=0.517]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 74.55it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 11:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]         
    Epoch 12:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:   8%|▊         | 1/13 [00:00<00:00, 84.06it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:   8%|▊         | 1/13 [00:00<00:00, 82.64it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  15%|█▌        | 2/13 [00:00<00:00, 83.86it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  15%|█▌        | 2/13 [00:00<00:00, 83.14it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  23%|██▎       | 3/13 [00:00<00:00, 84.49it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  23%|██▎       | 3/13 [00:00<00:00, 83.95it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  31%|███       | 4/13 [00:00<00:00, 83.59it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  31%|███       | 4/13 [00:00<00:00, 83.18it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  38%|███▊      | 5/13 [00:00<00:00, 83.46it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  38%|███▊      | 5/13 [00:00<00:00, 83.17it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  46%|████▌     | 6/13 [00:00<00:00, 83.64it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  46%|████▌     | 6/13 [00:00<00:00, 83.40it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  54%|█████▍    | 7/13 [00:00<00:00, 84.00it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  54%|█████▍    | 7/13 [00:00<00:00, 83.79it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  62%|██████▏   | 8/13 [00:00<00:00, 84.03it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  62%|██████▏   | 8/13 [00:00<00:00, 83.85it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  69%|██████▉   | 9/13 [00:00<00:00, 83.85it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  69%|██████▉   | 9/13 [00:00<00:00, 83.67it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  77%|███████▋  | 10/13 [00:00<00:00, 83.97it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  77%|███████▋  | 10/13 [00:00<00:00, 83.82it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  85%|████████▍ | 11/13 [00:00<00:00, 84.06it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  85%|████████▍ | 11/13 [00:00<00:00, 83.93it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  92%|█████████▏| 12/13 [00:00<00:00, 84.18it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12:  92%|█████████▏| 12/13 [00:00<00:00, 84.04it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 84.60it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 84.49it/s, v_num=ld_0, val_loss=0.537, train_loss=0.527]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 76.84it/s, v_num=ld_0, val_loss=0.536, train_loss=0.527]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 76.56it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 12:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]         
    Epoch 13:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:   8%|▊         | 1/13 [00:00<00:00, 81.07it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:   8%|▊         | 1/13 [00:00<00:00, 79.75it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  15%|█▌        | 2/13 [00:00<00:00, 82.87it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  15%|█▌        | 2/13 [00:00<00:00, 82.09it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  23%|██▎       | 3/13 [00:00<00:00, 83.49it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  23%|██▎       | 3/13 [00:00<00:00, 83.02it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  31%|███       | 4/13 [00:00<00:00, 83.36it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  31%|███       | 4/13 [00:00<00:00, 82.99it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  38%|███▊      | 5/13 [00:00<00:00, 83.51it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  38%|███▊      | 5/13 [00:00<00:00, 83.22it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  46%|████▌     | 6/13 [00:00<00:00, 82.90it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  46%|████▌     | 6/13 [00:00<00:00, 82.64it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  54%|█████▍    | 7/13 [00:00<00:00, 83.12it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  54%|█████▍    | 7/13 [00:00<00:00, 82.89it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  62%|██████▏   | 8/13 [00:00<00:00, 83.41it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  62%|██████▏   | 8/13 [00:00<00:00, 83.23it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  69%|██████▉   | 9/13 [00:00<00:00, 83.58it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  69%|██████▉   | 9/13 [00:00<00:00, 83.42it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  77%|███████▋  | 10/13 [00:00<00:00, 83.69it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  77%|███████▋  | 10/13 [00:00<00:00, 83.54it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  85%|████████▍ | 11/13 [00:00<00:00, 83.55it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  85%|████████▍ | 11/13 [00:00<00:00, 83.40it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  92%|█████████▏| 12/13 [00:00<00:00, 83.38it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:  92%|█████████▏| 12/13 [00:00<00:00, 83.26it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 83.80it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 83.68it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 76.13it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 75.85it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 13:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]         
    Epoch 14:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:   8%|▊         | 1/13 [00:00<00:00, 81.54it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:   8%|▊         | 1/13 [00:00<00:00, 80.20it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  15%|█▌        | 2/13 [00:00<00:00, 80.33it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  15%|█▌        | 2/13 [00:00<00:00, 79.60it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  23%|██▎       | 3/13 [00:00<00:00, 81.34it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  23%|██▎       | 3/13 [00:00<00:00, 80.89it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  31%|███       | 4/13 [00:00<00:00, 82.07it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  31%|███       | 4/13 [00:00<00:00, 81.72it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  38%|███▊      | 5/13 [00:00<00:00, 82.20it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  38%|███▊      | 5/13 [00:00<00:00, 81.92it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  46%|████▌     | 6/13 [00:00<00:00, 82.55it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  46%|████▌     | 6/13 [00:00<00:00, 82.31it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  54%|█████▍    | 7/13 [00:00<00:00, 82.32it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  54%|█████▍    | 7/13 [00:00<00:00, 82.09it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  62%|██████▏   | 8/13 [00:00<00:00, 82.49it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  62%|██████▏   | 8/13 [00:00<00:00, 82.29it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  69%|██████▉   | 9/13 [00:00<00:00, 82.63it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  69%|██████▉   | 9/13 [00:00<00:00, 82.47it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  77%|███████▋  | 10/13 [00:00<00:00, 82.86it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  77%|███████▋  | 10/13 [00:00<00:00, 82.72it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  85%|████████▍ | 11/13 [00:00<00:00, 82.55it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  85%|████████▍ | 11/13 [00:00<00:00, 82.41it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  92%|█████████▏| 12/13 [00:00<00:00, 82.51it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14:  92%|█████████▏| 12/13 [00:00<00:00, 82.38it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 82.98it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 82.87it/s, v_num=ld_0, val_loss=0.536, train_loss=0.515]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 75.54it/s, v_num=ld_0, val_loss=0.543, train_loss=0.515]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 75.28it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 14:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]         
    Epoch 15:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:   8%|▊         | 1/13 [00:00<00:00, 85.07it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:   8%|▊         | 1/13 [00:00<00:00, 83.47it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  15%|█▌        | 2/13 [00:00<00:00, 84.14it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  15%|█▌        | 2/13 [00:00<00:00, 83.35it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  23%|██▎       | 3/13 [00:00<00:00, 84.00it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  23%|██▎       | 3/13 [00:00<00:00, 83.48it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  31%|███       | 4/13 [00:00<00:00, 83.51it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  31%|███       | 4/13 [00:00<00:00, 83.08it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  38%|███▊      | 5/13 [00:00<00:00, 83.72it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  38%|███▊      | 5/13 [00:00<00:00, 83.41it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  46%|████▌     | 6/13 [00:00<00:00, 83.88it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  46%|████▌     | 6/13 [00:00<00:00, 83.64it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  54%|█████▍    | 7/13 [00:00<00:00, 83.97it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  54%|█████▍    | 7/13 [00:00<00:00, 83.77it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  62%|██████▏   | 8/13 [00:00<00:00, 84.05it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  62%|██████▏   | 8/13 [00:00<00:00, 83.87it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  69%|██████▉   | 9/13 [00:00<00:00, 83.60it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  69%|██████▉   | 9/13 [00:00<00:00, 83.43it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  77%|███████▋  | 10/13 [00:00<00:00, 83.70it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  77%|███████▋  | 10/13 [00:00<00:00, 83.56it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  85%|████████▍ | 11/13 [00:00<00:00, 83.82it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  85%|████████▍ | 11/13 [00:00<00:00, 83.68it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  92%|█████████▏| 12/13 [00:00<00:00, 83.96it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15:  92%|█████████▏| 12/13 [00:00<00:00, 83.84it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 84.39it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 84.28it/s, v_num=ld_0, val_loss=0.543, train_loss=0.509]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 76.49it/s, v_num=ld_0, val_loss=0.537, train_loss=0.509]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 76.23it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 15:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]         
    Epoch 16:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:   8%|▊         | 1/13 [00:00<00:00, 80.51it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:   8%|▊         | 1/13 [00:00<00:00, 79.16it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  15%|█▌        | 2/13 [00:00<00:00, 82.14it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  15%|█▌        | 2/13 [00:00<00:00, 81.46it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  23%|██▎       | 3/13 [00:00<00:00, 82.03it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  23%|██▎       | 3/13 [00:00<00:00, 81.53it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  31%|███       | 4/13 [00:00<00:00, 83.11it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  31%|███       | 4/13 [00:00<00:00, 82.76it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  38%|███▊      | 5/13 [00:00<00:00, 83.65it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  38%|███▊      | 5/13 [00:00<00:00, 83.33it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  46%|████▌     | 6/13 [00:00<00:00, 82.66it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  46%|████▌     | 6/13 [00:00<00:00, 82.40it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  54%|█████▍    | 7/13 [00:00<00:00, 81.37it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  54%|█████▍    | 7/13 [00:00<00:00, 81.08it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  62%|██████▏   | 8/13 [00:00<00:00, 80.49it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  62%|██████▏   | 8/13 [00:00<00:00, 80.32it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  69%|██████▉   | 9/13 [00:00<00:00, 80.74it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  69%|██████▉   | 9/13 [00:00<00:00, 80.59it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  77%|███████▋  | 10/13 [00:00<00:00, 81.13it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  77%|███████▋  | 10/13 [00:00<00:00, 80.99it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  85%|████████▍ | 11/13 [00:00<00:00, 80.89it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  85%|████████▍ | 11/13 [00:00<00:00, 80.75it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  92%|█████████▏| 12/13 [00:00<00:00, 79.91it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16:  92%|█████████▏| 12/13 [00:00<00:00, 79.80it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 79.97it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 79.86it/s, v_num=ld_0, val_loss=0.537, train_loss=0.507]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 72.96it/s, v_num=ld_0, val_loss=0.530, train_loss=0.507]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 72.71it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 16:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]         
    Epoch 17:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:   8%|▊         | 1/13 [00:00<00:00, 80.42it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:   8%|▊         | 1/13 [00:00<00:00, 79.08it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  15%|█▌        | 2/13 [00:00<00:00, 80.06it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  15%|█▌        | 2/13 [00:00<00:00, 79.32it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  23%|██▎       | 3/13 [00:00<00:00, 78.39it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  23%|██▎       | 3/13 [00:00<00:00, 77.86it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  31%|███       | 4/13 [00:00<00:00, 78.24it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  31%|███       | 4/13 [00:00<00:00, 77.85it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  38%|███▊      | 5/13 [00:00<00:00, 78.73it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  38%|███▊      | 5/13 [00:00<00:00, 78.44it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  46%|████▌     | 6/13 [00:00<00:00, 78.86it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  46%|████▌     | 6/13 [00:00<00:00, 78.61it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  54%|█████▍    | 7/13 [00:00<00:00, 79.26it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  54%|█████▍    | 7/13 [00:00<00:00, 79.07it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  62%|██████▏   | 8/13 [00:00<00:00, 78.17it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  62%|██████▏   | 8/13 [00:00<00:00, 77.99it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  69%|██████▉   | 9/13 [00:00<00:00, 78.02it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  69%|██████▉   | 9/13 [00:00<00:00, 77.88it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  77%|███████▋  | 10/13 [00:00<00:00, 78.30it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  77%|███████▋  | 10/13 [00:00<00:00, 78.17it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  85%|████████▍ | 11/13 [00:00<00:00, 78.74it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  85%|████████▍ | 11/13 [00:00<00:00, 78.62it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  92%|█████████▏| 12/13 [00:00<00:00, 79.07it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17:  92%|█████████▏| 12/13 [00:00<00:00, 78.96it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 79.43it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 79.32it/s, v_num=ld_0, val_loss=0.530, train_loss=0.503]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 72.43it/s, v_num=ld_0, val_loss=0.525, train_loss=0.503]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 72.18it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 17:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]         
    Epoch 18:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:   8%|▊         | 1/13 [00:00<00:00, 80.40it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:   8%|▊         | 1/13 [00:00<00:00, 79.07it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  15%|█▌        | 2/13 [00:00<00:00, 80.80it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  15%|█▌        | 2/13 [00:00<00:00, 80.13it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  23%|██▎       | 3/13 [00:00<00:00, 81.94it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  23%|██▎       | 3/13 [00:00<00:00, 81.48it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  31%|███       | 4/13 [00:00<00:00, 82.45it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  31%|███       | 4/13 [00:00<00:00, 82.10it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  38%|███▊      | 5/13 [00:00<00:00, 82.25it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  38%|███▊      | 5/13 [00:00<00:00, 81.97it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  46%|████▌     | 6/13 [00:00<00:00, 82.26it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  46%|████▌     | 6/13 [00:00<00:00, 82.02it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  54%|█████▍    | 7/13 [00:00<00:00, 82.59it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  54%|█████▍    | 7/13 [00:00<00:00, 82.39it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  62%|██████▏   | 8/13 [00:00<00:00, 82.79it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  62%|██████▏   | 8/13 [00:00<00:00, 82.61it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  69%|██████▉   | 9/13 [00:00<00:00, 82.85it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  69%|██████▉   | 9/13 [00:00<00:00, 82.69it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  77%|███████▋  | 10/13 [00:00<00:00, 81.97it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  77%|███████▋  | 10/13 [00:00<00:00, 81.76it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  85%|████████▍ | 11/13 [00:00<00:00, 81.85it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  85%|████████▍ | 11/13 [00:00<00:00, 81.73it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  92%|█████████▏| 12/13 [00:00<00:00, 81.85it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18:  92%|█████████▏| 12/13 [00:00<00:00, 81.74it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 81.97it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 81.87it/s, v_num=ld_0, val_loss=0.525, train_loss=0.507]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 74.43it/s, v_num=ld_0, val_loss=0.568, train_loss=0.507]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 74.18it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 18:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]         
    Epoch 19:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:   8%|▊         | 1/13 [00:00<00:00, 78.90it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:   8%|▊         | 1/13 [00:00<00:00, 77.50it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  15%|█▌        | 2/13 [00:00<00:00, 76.26it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  15%|█▌        | 2/13 [00:00<00:00, 75.49it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  23%|██▎       | 3/13 [00:00<00:00, 77.97it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  23%|██▎       | 3/13 [00:00<00:00, 77.51it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  31%|███       | 4/13 [00:00<00:00, 78.76it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  31%|███       | 4/13 [00:00<00:00, 78.43it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  38%|███▊      | 5/13 [00:00<00:00, 79.45it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  38%|███▊      | 5/13 [00:00<00:00, 79.18it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  46%|████▌     | 6/13 [00:00<00:00, 79.94it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  46%|████▌     | 6/13 [00:00<00:00, 79.72it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  54%|█████▍    | 7/13 [00:00<00:00, 79.69it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  54%|█████▍    | 7/13 [00:00<00:00, 79.48it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  62%|██████▏   | 8/13 [00:00<00:00, 79.45it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  62%|██████▏   | 8/13 [00:00<00:00, 79.29it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  69%|██████▉   | 9/13 [00:00<00:00, 79.62it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  69%|██████▉   | 9/13 [00:00<00:00, 79.47it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  77%|███████▋  | 10/13 [00:00<00:00, 79.85it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  77%|███████▋  | 10/13 [00:00<00:00, 79.70it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  85%|████████▍ | 11/13 [00:00<00:00, 80.14it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  85%|████████▍ | 11/13 [00:00<00:00, 80.00it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  92%|█████████▏| 12/13 [00:00<00:00, 80.07it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19:  92%|█████████▏| 12/13 [00:00<00:00, 79.94it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 80.56it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 80.44it/s, v_num=ld_0, val_loss=0.568, train_loss=0.514]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 73.38it/s, v_num=ld_0, val_loss=0.536, train_loss=0.514]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 73.10it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 19:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]         
    Epoch 20:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:   8%|▊         | 1/13 [00:00<00:00, 82.16it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:   8%|▊         | 1/13 [00:00<00:00, 80.81it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  15%|█▌        | 2/13 [00:00<00:00, 83.39it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  15%|█▌        | 2/13 [00:00<00:00, 82.61it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  23%|██▎       | 3/13 [00:00<00:00, 83.61it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  23%|██▎       | 3/13 [00:00<00:00, 83.08it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  31%|███       | 4/13 [00:00<00:00, 82.40it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  31%|███       | 4/13 [00:00<00:00, 82.03it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  38%|███▊      | 5/13 [00:00<00:00, 81.56it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  38%|███▊      | 5/13 [00:00<00:00, 81.29it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  46%|████▌     | 6/13 [00:00<00:00, 80.68it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  46%|████▌     | 6/13 [00:00<00:00, 80.46it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  54%|█████▍    | 7/13 [00:00<00:00, 81.26it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  54%|█████▍    | 7/13 [00:00<00:00, 81.07it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  62%|██████▏   | 8/13 [00:00<00:00, 81.28it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  62%|██████▏   | 8/13 [00:00<00:00, 81.11it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  69%|██████▉   | 9/13 [00:00<00:00, 81.29it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  69%|██████▉   | 9/13 [00:00<00:00, 81.11it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  77%|███████▋  | 10/13 [00:00<00:00, 80.79it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  77%|███████▋  | 10/13 [00:00<00:00, 80.66it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  85%|████████▍ | 11/13 [00:00<00:00, 80.34it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  85%|████████▍ | 11/13 [00:00<00:00, 80.20it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  92%|█████████▏| 12/13 [00:00<00:00, 80.52it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20:  92%|█████████▏| 12/13 [00:00<00:00, 80.41it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 81.08it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 80.98it/s, v_num=ld_0, val_loss=0.536, train_loss=0.541]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 73.92it/s, v_num=ld_0, val_loss=0.558, train_loss=0.541]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 73.67it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 20:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]         
    Epoch 21:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:   8%|▊         | 1/13 [00:00<00:00, 72.11it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:   8%|▊         | 1/13 [00:00<00:00, 70.87it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  15%|█▌        | 2/13 [00:00<00:00, 76.74it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  15%|█▌        | 2/13 [00:00<00:00, 76.14it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  23%|██▎       | 3/13 [00:00<00:00, 77.88it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  23%|██▎       | 3/13 [00:00<00:00, 77.46it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  31%|███       | 4/13 [00:00<00:00, 78.70it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  31%|███       | 4/13 [00:00<00:00, 78.34it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  38%|███▊      | 5/13 [00:00<00:00, 78.00it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  38%|███▊      | 5/13 [00:00<00:00, 77.73it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  46%|████▌     | 6/13 [00:00<00:00, 77.83it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  46%|████▌     | 6/13 [00:00<00:00, 77.59it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  54%|█████▍    | 7/13 [00:00<00:00, 78.47it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  54%|█████▍    | 7/13 [00:00<00:00, 78.29it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  62%|██████▏   | 8/13 [00:00<00:00, 78.36it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  62%|██████▏   | 8/13 [00:00<00:00, 78.20it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  69%|██████▉   | 9/13 [00:00<00:00, 78.93it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  69%|██████▉   | 9/13 [00:00<00:00, 78.79it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  77%|███████▋  | 10/13 [00:00<00:00, 79.24it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  77%|███████▋  | 10/13 [00:00<00:00, 79.11it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  85%|████████▍ | 11/13 [00:00<00:00, 79.13it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  85%|████████▍ | 11/13 [00:00<00:00, 79.00it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  92%|█████████▏| 12/13 [00:00<00:00, 79.15it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21:  92%|█████████▏| 12/13 [00:00<00:00, 79.04it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 79.57it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 79.47it/s, v_num=ld_0, val_loss=0.558, train_loss=0.528]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 72.66it/s, v_num=ld_0, val_loss=0.543, train_loss=0.528]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 72.41it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 21:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]         
    Epoch 22:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:   8%|▊         | 1/13 [00:00<00:00, 85.23it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:   8%|▊         | 1/13 [00:00<00:00, 83.63it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  15%|█▌        | 2/13 [00:00<00:00, 84.63it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  15%|█▌        | 2/13 [00:00<00:00, 83.84it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  23%|██▎       | 3/13 [00:00<00:00, 79.03it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  23%|██▎       | 3/13 [00:00<00:00, 78.55it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  31%|███       | 4/13 [00:00<00:00, 80.03it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  31%|███       | 4/13 [00:00<00:00, 79.69it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  38%|███▊      | 5/13 [00:00<00:00, 80.13it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  38%|███▊      | 5/13 [00:00<00:00, 79.86it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  46%|████▌     | 6/13 [00:00<00:00, 79.64it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  46%|████▌     | 6/13 [00:00<00:00, 79.42it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  54%|█████▍    | 7/13 [00:00<00:00, 80.17it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  54%|█████▍    | 7/13 [00:00<00:00, 79.98it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  62%|██████▏   | 8/13 [00:00<00:00, 79.49it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  62%|██████▏   | 8/13 [00:00<00:00, 79.29it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  69%|██████▉   | 9/13 [00:00<00:00, 79.33it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  69%|██████▉   | 9/13 [00:00<00:00, 79.18it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  77%|███████▋  | 10/13 [00:00<00:00, 79.84it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  77%|███████▋  | 10/13 [00:00<00:00, 79.71it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  85%|████████▍ | 11/13 [00:00<00:00, 80.14it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  85%|████████▍ | 11/13 [00:00<00:00, 80.01it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  92%|█████████▏| 12/13 [00:00<00:00, 79.58it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22:  92%|█████████▏| 12/13 [00:00<00:00, 79.45it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 79.30it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 79.17it/s, v_num=ld_0, val_loss=0.543, train_loss=0.524]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 72.29it/s, v_num=ld_0, val_loss=0.533, train_loss=0.524]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 72.04it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 22:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]         
    Epoch 23:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:   8%|▊         | 1/13 [00:00<00:00, 71.09it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:   8%|▊         | 1/13 [00:00<00:00, 70.06it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  15%|█▌        | 2/13 [00:00<00:00, 76.16it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  15%|█▌        | 2/13 [00:00<00:00, 75.56it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  23%|██▎       | 3/13 [00:00<00:00, 77.80it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  23%|██▎       | 3/13 [00:00<00:00, 77.34it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  31%|███       | 4/13 [00:00<00:00, 78.90it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  31%|███       | 4/13 [00:00<00:00, 78.58it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  38%|███▊      | 5/13 [00:00<00:00, 77.98it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  38%|███▊      | 5/13 [00:00<00:00, 77.73it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  46%|████▌     | 6/13 [00:00<00:00, 79.01it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  46%|████▌     | 6/13 [00:00<00:00, 78.80it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  54%|█████▍    | 7/13 [00:00<00:00, 77.18it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  54%|█████▍    | 7/13 [00:00<00:00, 77.01it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  62%|██████▏   | 8/13 [00:00<00:00, 76.21it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  62%|██████▏   | 8/13 [00:00<00:00, 76.06it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  69%|██████▉   | 9/13 [00:00<00:00, 76.66it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  69%|██████▉   | 9/13 [00:00<00:00, 76.53it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  77%|███████▋  | 10/13 [00:00<00:00, 76.83it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  77%|███████▋  | 10/13 [00:00<00:00, 76.70it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  85%|████████▍ | 11/13 [00:00<00:00, 76.94it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  85%|████████▍ | 11/13 [00:00<00:00, 76.83it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  92%|█████████▏| 12/13 [00:00<00:00, 76.95it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23:  92%|█████████▏| 12/13 [00:00<00:00, 76.85it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 77.73it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 77.64it/s, v_num=ld_0, val_loss=0.533, train_loss=0.510]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 71.10it/s, v_num=ld_0, val_loss=0.532, train_loss=0.510]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 70.87it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 23:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]         
    Epoch 24:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:   8%|▊         | 1/13 [00:00<00:00, 82.00it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:   8%|▊         | 1/13 [00:00<00:00, 80.65it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  15%|█▌        | 2/13 [00:00<00:00, 81.70it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  15%|█▌        | 2/13 [00:00<00:00, 80.90it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  23%|██▎       | 3/13 [00:00<00:00, 81.47it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  23%|██▎       | 3/13 [00:00<00:00, 81.02it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  31%|███       | 4/13 [00:00<00:00, 82.12it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  31%|███       | 4/13 [00:00<00:00, 81.78it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  38%|███▊      | 5/13 [00:00<00:00, 82.77it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  38%|███▊      | 5/13 [00:00<00:00, 82.44it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  46%|████▌     | 6/13 [00:00<00:00, 82.36it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  46%|████▌     | 6/13 [00:00<00:00, 82.13it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  54%|█████▍    | 7/13 [00:00<00:00, 82.13it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  54%|█████▍    | 7/13 [00:00<00:00, 81.92it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  62%|██████▏   | 8/13 [00:00<00:00, 82.42it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  62%|██████▏   | 8/13 [00:00<00:00, 82.24it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  69%|██████▉   | 9/13 [00:00<00:00, 82.63it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  69%|██████▉   | 9/13 [00:00<00:00, 82.47it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  77%|███████▋  | 10/13 [00:00<00:00, 82.53it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  77%|███████▋  | 10/13 [00:00<00:00, 82.39it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  85%|████████▍ | 11/13 [00:00<00:00, 82.57it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  85%|████████▍ | 11/13 [00:00<00:00, 82.44it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  92%|█████████▏| 12/13 [00:00<00:00, 82.35it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24:  92%|█████████▏| 12/13 [00:00<00:00, 82.23it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 82.74it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 82.63it/s, v_num=ld_0, val_loss=0.532, train_loss=0.518]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 75.22it/s, v_num=ld_0, val_loss=0.576, train_loss=0.518]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 74.92it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 24:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]         
    Epoch 25:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:   8%|▊         | 1/13 [00:00<00:00, 79.41it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:   8%|▊         | 1/13 [00:00<00:00, 78.14it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  15%|█▌        | 2/13 [00:00<00:00, 80.29it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  15%|█▌        | 2/13 [00:00<00:00, 79.63it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  23%|██▎       | 3/13 [00:00<00:00, 81.74it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  23%|██▎       | 3/13 [00:00<00:00, 81.29it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  31%|███       | 4/13 [00:00<00:00, 81.27it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  31%|███       | 4/13 [00:00<00:00, 80.92it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  38%|███▊      | 5/13 [00:00<00:00, 82.03it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  38%|███▊      | 5/13 [00:00<00:00, 81.75it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  46%|████▌     | 6/13 [00:00<00:00, 80.65it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  46%|████▌     | 6/13 [00:00<00:00, 80.41it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  54%|█████▍    | 7/13 [00:00<00:00, 81.15it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  54%|█████▍    | 7/13 [00:00<00:00, 80.92it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  62%|██████▏   | 8/13 [00:00<00:00, 81.01it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  62%|██████▏   | 8/13 [00:00<00:00, 80.84it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  69%|██████▉   | 9/13 [00:00<00:00, 80.61it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  69%|██████▉   | 9/13 [00:00<00:00, 80.45it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  77%|███████▋  | 10/13 [00:00<00:00, 80.24it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  77%|███████▋  | 10/13 [00:00<00:00, 80.11it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  85%|████████▍ | 11/13 [00:00<00:00, 80.44it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  85%|████████▍ | 11/13 [00:00<00:00, 80.32it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  92%|█████████▏| 12/13 [00:00<00:00, 80.86it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25:  92%|█████████▏| 12/13 [00:00<00:00, 80.72it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 81.34it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 81.23it/s, v_num=ld_0, val_loss=0.576, train_loss=0.575]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 74.19it/s, v_num=ld_0, val_loss=0.556, train_loss=0.575]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 73.93it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 25:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]         
    Epoch 26:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:   8%|▊         | 1/13 [00:00<00:00, 76.94it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:   8%|▊         | 1/13 [00:00<00:00, 75.62it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  15%|█▌        | 2/13 [00:00<00:00, 77.46it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  15%|█▌        | 2/13 [00:00<00:00, 76.76it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  23%|██▎       | 3/13 [00:00<00:00, 78.08it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  23%|██▎       | 3/13 [00:00<00:00, 77.67it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  31%|███       | 4/13 [00:00<00:00, 77.13it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  31%|███       | 4/13 [00:00<00:00, 76.79it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  38%|███▊      | 5/13 [00:00<00:00, 78.64it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  38%|███▊      | 5/13 [00:00<00:00, 78.39it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  46%|████▌     | 6/13 [00:00<00:00, 74.97it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  46%|████▌     | 6/13 [00:00<00:00, 74.75it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  54%|█████▍    | 7/13 [00:00<00:00, 74.92it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  54%|█████▍    | 7/13 [00:00<00:00, 74.76it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  62%|██████▏   | 8/13 [00:00<00:00, 76.08it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  62%|██████▏   | 8/13 [00:00<00:00, 75.93it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  69%|██████▉   | 9/13 [00:00<00:00, 76.57it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  69%|██████▉   | 9/13 [00:00<00:00, 76.44it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  77%|███████▋  | 10/13 [00:00<00:00, 77.08it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  77%|███████▋  | 10/13 [00:00<00:00, 76.95it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  85%|████████▍ | 11/13 [00:00<00:00, 75.32it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  85%|████████▍ | 11/13 [00:00<00:00, 75.21it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  92%|█████████▏| 12/13 [00:00<00:00, 75.84it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26:  92%|█████████▏| 12/13 [00:00<00:00, 75.74it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26: 100%|██████████| 13/13 [00:00<00:00, 76.27it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26: 100%|██████████| 13/13 [00:00<00:00, 76.18it/s, v_num=ld_0, val_loss=0.556, train_loss=0.545]
    Epoch 26: 100%|██████████| 13/13 [00:00<00:00, 69.87it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 26: 100%|██████████| 13/13 [00:00<00:00, 69.65it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 26:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]         
    Epoch 27:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:   8%|▊         | 1/13 [00:00<00:00, 73.39it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:   8%|▊         | 1/13 [00:00<00:00, 72.21it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  15%|█▌        | 2/13 [00:00<00:00, 72.96it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  15%|█▌        | 2/13 [00:00<00:00, 72.42it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  23%|██▎       | 3/13 [00:00<00:00, 73.55it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  23%|██▎       | 3/13 [00:00<00:00, 73.16it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  31%|███       | 4/13 [00:00<00:00, 75.93it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  31%|███       | 4/13 [00:00<00:00, 75.61it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  38%|███▊      | 5/13 [00:00<00:00, 74.72it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  38%|███▊      | 5/13 [00:00<00:00, 74.49it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  46%|████▌     | 6/13 [00:00<00:00, 76.14it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  46%|████▌     | 6/13 [00:00<00:00, 75.94it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  54%|█████▍    | 7/13 [00:00<00:00, 77.57it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  54%|█████▍    | 7/13 [00:00<00:00, 77.39it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  62%|██████▏   | 8/13 [00:00<00:00, 76.64it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  62%|██████▏   | 8/13 [00:00<00:00, 76.46it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  69%|██████▉   | 9/13 [00:00<00:00, 76.81it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  69%|██████▉   | 9/13 [00:00<00:00, 76.65it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  77%|███████▋  | 10/13 [00:00<00:00, 76.77it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  77%|███████▋  | 10/13 [00:00<00:00, 76.64it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  85%|████████▍ | 11/13 [00:00<00:00, 76.84it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  85%|████████▍ | 11/13 [00:00<00:00, 76.72it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  92%|█████████▏| 12/13 [00:00<00:00, 77.02it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27:  92%|█████████▏| 12/13 [00:00<00:00, 76.92it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27: 100%|██████████| 13/13 [00:00<00:00, 75.63it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27: 100%|██████████| 13/13 [00:00<00:00, 75.53it/s, v_num=ld_0, val_loss=0.562, train_loss=0.545]
    Epoch 27: 100%|██████████| 13/13 [00:00<00:00, 68.95it/s, v_num=ld_0, val_loss=0.622, train_loss=0.545]
    Epoch 27: 100%|██████████| 13/13 [00:00<00:00, 68.69it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 27:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]         
    Epoch 28:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:   8%|▊         | 1/13 [00:00<00:00, 67.08it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:   8%|▊         | 1/13 [00:00<00:00, 66.06it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  15%|█▌        | 2/13 [00:00<00:00, 73.37it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  15%|█▌        | 2/13 [00:00<00:00, 72.82it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  23%|██▎       | 3/13 [00:00<00:00, 72.41it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  23%|██▎       | 3/13 [00:00<00:00, 72.05it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  31%|███       | 4/13 [00:00<00:00, 75.60it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  31%|███       | 4/13 [00:00<00:00, 75.31it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  38%|███▊      | 5/13 [00:00<00:00, 76.37it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  38%|███▊      | 5/13 [00:00<00:00, 76.12it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  46%|████▌     | 6/13 [00:00<00:00, 77.96it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  46%|████▌     | 6/13 [00:00<00:00, 77.75it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  54%|█████▍    | 7/13 [00:00<00:00, 78.90it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  54%|█████▍    | 7/13 [00:00<00:00, 78.69it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  62%|██████▏   | 8/13 [00:00<00:00, 79.79it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  62%|██████▏   | 8/13 [00:00<00:00, 79.62it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  69%|██████▉   | 9/13 [00:00<00:00, 80.35it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  69%|██████▉   | 9/13 [00:00<00:00, 80.19it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  77%|███████▋  | 10/13 [00:00<00:00, 80.49it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  77%|███████▋  | 10/13 [00:00<00:00, 80.33it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  85%|████████▍ | 11/13 [00:00<00:00, 80.61it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  85%|████████▍ | 11/13 [00:00<00:00, 80.48it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  92%|█████████▏| 12/13 [00:00<00:00, 80.91it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28:  92%|█████████▏| 12/13 [00:00<00:00, 80.79it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28: 100%|██████████| 13/13 [00:00<00:00, 81.48it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28: 100%|██████████| 13/13 [00:00<00:00, 81.37it/s, v_num=ld_0, val_loss=0.622, train_loss=0.559]
    Epoch 28: 100%|██████████| 13/13 [00:00<00:00, 74.11it/s, v_num=ld_0, val_loss=0.693, train_loss=0.559]
    Epoch 28: 100%|██████████| 13/13 [00:00<00:00, 73.84it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 28:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]         
    Epoch 29:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:   8%|▊         | 1/13 [00:00<00:00, 83.22it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:   8%|▊         | 1/13 [00:00<00:00, 81.68it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  15%|█▌        | 2/13 [00:00<00:00, 82.16it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  15%|█▌        | 2/13 [00:00<00:00, 81.41it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  23%|██▎       | 3/13 [00:00<00:00, 83.40it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  23%|██▎       | 3/13 [00:00<00:00, 82.89it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  31%|███       | 4/13 [00:00<00:00, 84.06it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  31%|███       | 4/13 [00:00<00:00, 83.70it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  38%|███▊      | 5/13 [00:00<00:00, 84.52it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  38%|███▊      | 5/13 [00:00<00:00, 84.22it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  46%|████▌     | 6/13 [00:00<00:00, 84.81it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  46%|████▌     | 6/13 [00:00<00:00, 84.57it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  54%|█████▍    | 7/13 [00:00<00:00, 84.63it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  54%|█████▍    | 7/13 [00:00<00:00, 84.39it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  62%|██████▏   | 8/13 [00:00<00:00, 84.50it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  62%|██████▏   | 8/13 [00:00<00:00, 84.28it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  69%|██████▉   | 9/13 [00:00<00:00, 84.43it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  69%|██████▉   | 9/13 [00:00<00:00, 84.25it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  77%|███████▋  | 10/13 [00:00<00:00, 82.98it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  77%|███████▋  | 10/13 [00:00<00:00, 82.76it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  85%|████████▍ | 11/13 [00:00<00:00, 82.22it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  85%|████████▍ | 11/13 [00:00<00:00, 82.07it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  92%|█████████▏| 12/13 [00:00<00:00, 81.73it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29:  92%|█████████▏| 12/13 [00:00<00:00, 81.58it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29: 100%|██████████| 13/13 [00:00<00:00, 82.12it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29: 100%|██████████| 13/13 [00:00<00:00, 82.01it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29: 100%|██████████| 13/13 [00:00<00:00, 74.60it/s, v_num=ld_0, val_loss=0.693, train_loss=0.689]
    Epoch 29: 100%|██████████| 13/13 [00:00<00:00, 74.26it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 29:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]         
    Epoch 30:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:   8%|▊         | 1/13 [00:00<00:00, 84.70it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:   8%|▊         | 1/13 [00:00<00:00, 83.27it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  15%|█▌        | 2/13 [00:00<00:00, 83.79it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  15%|█▌        | 2/13 [00:00<00:00, 83.07it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  23%|██▎       | 3/13 [00:00<00:00, 82.93it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  23%|██▎       | 3/13 [00:00<00:00, 82.34it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  31%|███       | 4/13 [00:00<00:00, 81.85it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  31%|███       | 4/13 [00:00<00:00, 81.46it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  38%|███▊      | 5/13 [00:00<00:00, 82.38it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  38%|███▊      | 5/13 [00:00<00:00, 82.09it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  46%|████▌     | 6/13 [00:00<00:00, 82.82it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  46%|████▌     | 6/13 [00:00<00:00, 82.55it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  54%|█████▍    | 7/13 [00:00<00:00, 83.14it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  54%|█████▍    | 7/13 [00:00<00:00, 82.90it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  62%|██████▏   | 8/13 [00:00<00:00, 82.85it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  62%|██████▏   | 8/13 [00:00<00:00, 82.67it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  69%|██████▉   | 9/13 [00:00<00:00, 82.67it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  69%|██████▉   | 9/13 [00:00<00:00, 82.50it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  77%|███████▋  | 10/13 [00:00<00:00, 82.97it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  77%|███████▋  | 10/13 [00:00<00:00, 82.83it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  85%|████████▍ | 11/13 [00:00<00:00, 83.07it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  85%|████████▍ | 11/13 [00:00<00:00, 82.90it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  92%|█████████▏| 12/13 [00:00<00:00, 82.84it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:  92%|█████████▏| 12/13 [00:00<00:00, 82.70it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30: 100%|██████████| 13/13 [00:00<00:00, 82.87it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30: 100%|██████████| 13/13 [00:00<00:00, 82.75it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30: 100%|██████████| 13/13 [00:00<00:00, 75.02it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30: 100%|██████████| 13/13 [00:00<00:00, 74.73it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 30:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]         
    Epoch 31:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:   8%|▊         | 1/13 [00:00<00:00, 75.01it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:   8%|▊         | 1/13 [00:00<00:00, 73.72it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  15%|█▌        | 2/13 [00:00<00:00, 79.15it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  15%|█▌        | 2/13 [00:00<00:00, 78.51it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  23%|██▎       | 3/13 [00:00<00:00, 81.10it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  23%|██▎       | 3/13 [00:00<00:00, 80.65it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  31%|███       | 4/13 [00:00<00:00, 82.46it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  31%|███       | 4/13 [00:00<00:00, 82.11it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  38%|███▊      | 5/13 [00:00<00:00, 83.21it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  38%|███▊      | 5/13 [00:00<00:00, 82.91it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  46%|████▌     | 6/13 [00:00<00:00, 82.95it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  46%|████▌     | 6/13 [00:00<00:00, 82.69it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  54%|█████▍    | 7/13 [00:00<00:00, 83.37it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  54%|█████▍    | 7/13 [00:00<00:00, 83.16it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  62%|██████▏   | 8/13 [00:00<00:00, 83.80it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  62%|██████▏   | 8/13 [00:00<00:00, 83.62it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  69%|██████▉   | 9/13 [00:00<00:00, 84.10it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  69%|██████▉   | 9/13 [00:00<00:00, 83.92it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  77%|███████▋  | 10/13 [00:00<00:00, 84.28it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  77%|███████▋  | 10/13 [00:00<00:00, 84.12it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  85%|████████▍ | 11/13 [00:00<00:00, 84.07it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  85%|████████▍ | 11/13 [00:00<00:00, 83.92it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  92%|█████████▏| 12/13 [00:00<00:00, 84.17it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:  92%|█████████▏| 12/13 [00:00<00:00, 84.03it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31: 100%|██████████| 13/13 [00:00<00:00, 84.63it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31: 100%|██████████| 13/13 [00:00<00:00, 84.50it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31: 100%|██████████| 13/13 [00:00<00:00, 76.84it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31: 100%|██████████| 13/13 [00:00<00:00, 76.55it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 31:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]         
    Epoch 32:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:   8%|▊         | 1/13 [00:00<00:00, 85.00it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:   8%|▊         | 1/13 [00:00<00:00, 83.53it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  15%|█▌        | 2/13 [00:00<00:00, 85.36it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  15%|█▌        | 2/13 [00:00<00:00, 84.62it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  23%|██▎       | 3/13 [00:00<00:00, 84.33it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  23%|██▎       | 3/13 [00:00<00:00, 83.81it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  31%|███       | 4/13 [00:00<00:00, 84.61it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  31%|███       | 4/13 [00:00<00:00, 84.20it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  38%|███▊      | 5/13 [00:00<00:00, 85.01it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  38%|███▊      | 5/13 [00:00<00:00, 84.71it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  46%|████▌     | 6/13 [00:00<00:00, 84.85it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  46%|████▌     | 6/13 [00:00<00:00, 84.61it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  54%|█████▍    | 7/13 [00:00<00:00, 85.02it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  54%|█████▍    | 7/13 [00:00<00:00, 84.80it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  62%|██████▏   | 8/13 [00:00<00:00, 84.56it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  62%|██████▏   | 8/13 [00:00<00:00, 84.35it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  69%|██████▉   | 9/13 [00:00<00:00, 84.68it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  69%|██████▉   | 9/13 [00:00<00:00, 84.49it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  77%|███████▋  | 10/13 [00:00<00:00, 84.84it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  77%|███████▋  | 10/13 [00:00<00:00, 84.69it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  85%|████████▍ | 11/13 [00:00<00:00, 84.99it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  85%|████████▍ | 11/13 [00:00<00:00, 84.85it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  92%|█████████▏| 12/13 [00:00<00:00, 85.15it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32:  92%|█████████▏| 12/13 [00:00<00:00, 85.02it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32: 100%|██████████| 13/13 [00:00<00:00, 85.20it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32: 100%|██████████| 13/13 [00:00<00:00, 85.07it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32: 100%|██████████| 13/13 [00:00<00:00, 77.25it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32: 100%|██████████| 13/13 [00:00<00:00, 76.96it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    Epoch 32: 100%|██████████| 13/13 [00:00<00:00, 76.65it/s, v_num=ld_0, val_loss=0.693, train_loss=0.693]
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
         Validate metric           DataLoader 0
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
            AUROC_val                   0.5
          Accuracy_val          0.47999998927116394
            val_loss            0.6931471824645996
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────

    Training: |          | 0/? [00:00<?, ?it/s]
    Training:   0%|          | 0/13 [00:00<?, ?it/s]
    Epoch 0:   0%|          | 0/13 [00:00<?, ?it/s] 
    Epoch 0:   8%|▊         | 1/13 [00:00<00:00, 50.18it/s]
    Epoch 0:   8%|▊         | 1/13 [00:00<00:00, 49.37it/s, v_num=ld_1]
    Epoch 0:  15%|█▌        | 2/13 [00:00<00:00, 53.11it/s, v_num=ld_1]
    Epoch 0:  15%|█▌        | 2/13 [00:00<00:00, 52.65it/s, v_num=ld_1]
    Epoch 0:  23%|██▎       | 3/13 [00:00<00:00, 54.50it/s, v_num=ld_1]
    Epoch 0:  23%|██▎       | 3/13 [00:00<00:00, 54.18it/s, v_num=ld_1]
    Epoch 0:  31%|███       | 4/13 [00:00<00:00, 55.79it/s, v_num=ld_1]
    Epoch 0:  31%|███       | 4/13 [00:00<00:00, 55.61it/s, v_num=ld_1]
    Epoch 0:  38%|███▊      | 5/13 [00:00<00:00, 59.48it/s, v_num=ld_1]
    Epoch 0:  38%|███▊      | 5/13 [00:00<00:00, 59.31it/s, v_num=ld_1]
    Epoch 0:  46%|████▌     | 6/13 [00:00<00:00, 61.18it/s, v_num=ld_1]
    Epoch 0:  46%|████▌     | 6/13 [00:00<00:00, 61.02it/s, v_num=ld_1]
    Epoch 0:  54%|█████▍    | 7/13 [00:00<00:00, 63.57it/s, v_num=ld_1]
    Epoch 0:  54%|█████▍    | 7/13 [00:00<00:00, 63.44it/s, v_num=ld_1]
    Epoch 0:  62%|██████▏   | 8/13 [00:00<00:00, 65.41it/s, v_num=ld_1]
    Epoch 0:  62%|██████▏   | 8/13 [00:00<00:00, 65.29it/s, v_num=ld_1]
    Epoch 0:  69%|██████▉   | 9/13 [00:00<00:00, 66.90it/s, v_num=ld_1]
    Epoch 0:  69%|██████▉   | 9/13 [00:00<00:00, 66.78it/s, v_num=ld_1]
    Epoch 0:  77%|███████▋  | 10/13 [00:00<00:00, 68.15it/s, v_num=ld_1]
    Epoch 0:  77%|███████▋  | 10/13 [00:00<00:00, 68.05it/s, v_num=ld_1]
    Epoch 0:  85%|████████▍ | 11/13 [00:00<00:00, 68.87it/s, v_num=ld_1]
    Epoch 0:  85%|████████▍ | 11/13 [00:00<00:00, 68.78it/s, v_num=ld_1]
    Epoch 0:  92%|█████████▏| 12/13 [00:00<00:00, 69.77it/s, v_num=ld_1]
    Epoch 0:  92%|█████████▏| 12/13 [00:00<00:00, 69.69it/s, v_num=ld_1]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 70.76it/s, v_num=ld_1]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 70.67it/s, v_num=ld_1]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 64.85it/s, v_num=ld_1, val_loss=0.693]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 64.65it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 0:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]         
    Epoch 1:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:   8%|▊         | 1/13 [00:00<00:00, 80.88it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:   8%|▊         | 1/13 [00:00<00:00, 79.54it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  15%|█▌        | 2/13 [00:00<00:00, 78.47it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  15%|█▌        | 2/13 [00:00<00:00, 77.78it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  23%|██▎       | 3/13 [00:00<00:00, 76.64it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  23%|██▎       | 3/13 [00:00<00:00, 76.23it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  31%|███       | 4/13 [00:00<00:00, 70.20it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  31%|███       | 4/13 [00:00<00:00, 69.94it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  38%|███▊      | 5/13 [00:00<00:00, 61.01it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  38%|███▊      | 5/13 [00:00<00:00, 60.85it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  46%|████▌     | 6/13 [00:00<00:00, 51.43it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  46%|████▌     | 6/13 [00:00<00:00, 51.31it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  54%|█████▍    | 7/13 [00:00<00:00, 44.08it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  54%|█████▍    | 7/13 [00:00<00:00, 44.01it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  62%|██████▏   | 8/13 [00:00<00:00, 39.65it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  62%|██████▏   | 8/13 [00:00<00:00, 39.59it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  69%|██████▉   | 9/13 [00:00<00:00, 37.52it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  69%|██████▉   | 9/13 [00:00<00:00, 37.48it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  77%|███████▋  | 10/13 [00:00<00:00, 36.48it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  77%|███████▋  | 10/13 [00:00<00:00, 36.44it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  85%|████████▍ | 11/13 [00:00<00:00, 36.01it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  85%|████████▍ | 11/13 [00:00<00:00, 35.98it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  92%|█████████▏| 12/13 [00:00<00:00, 35.51it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1:  92%|█████████▏| 12/13 [00:00<00:00, 35.48it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 37.13it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 37.10it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 35.51it/s, v_num=ld_1, val_loss=0.693, train_loss=0.700]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 35.45it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 1:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]         
    Epoch 2:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:   8%|▊         | 1/13 [00:00<00:00, 83.26it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:   8%|▊         | 1/13 [00:00<00:00, 81.75it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  15%|█▌        | 2/13 [00:00<00:00, 83.55it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  15%|█▌        | 2/13 [00:00<00:00, 82.79it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  23%|██▎       | 3/13 [00:00<00:00, 82.56it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  23%|██▎       | 3/13 [00:00<00:00, 82.04it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  31%|███       | 4/13 [00:00<00:00, 83.07it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  31%|███       | 4/13 [00:00<00:00, 82.68it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  38%|███▊      | 5/13 [00:00<00:00, 83.43it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  38%|███▊      | 5/13 [00:00<00:00, 83.13it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  46%|████▌     | 6/13 [00:00<00:00, 83.61it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  46%|████▌     | 6/13 [00:00<00:00, 83.37it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  54%|█████▍    | 7/13 [00:00<00:00, 83.92it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  54%|█████▍    | 7/13 [00:00<00:00, 83.71it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  62%|██████▏   | 8/13 [00:00<00:00, 83.79it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  62%|██████▏   | 8/13 [00:00<00:00, 83.60it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  69%|██████▉   | 9/13 [00:00<00:00, 84.04it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  69%|██████▉   | 9/13 [00:00<00:00, 83.86it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  77%|███████▋  | 10/13 [00:00<00:00, 84.38it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  77%|███████▋  | 10/13 [00:00<00:00, 84.24it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  85%|████████▍ | 11/13 [00:00<00:00, 84.60it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  85%|████████▍ | 11/13 [00:00<00:00, 84.47it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  92%|█████████▏| 12/13 [00:00<00:00, 84.78it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:  92%|█████████▏| 12/13 [00:00<00:00, 84.65it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 84.88it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 84.75it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 77.02it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 76.74it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 2:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]         
    Epoch 3:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:   8%|▊         | 1/13 [00:00<00:00, 85.18it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:   8%|▊         | 1/13 [00:00<00:00, 83.73it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  15%|█▌        | 2/13 [00:00<00:00, 85.37it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  15%|█▌        | 2/13 [00:00<00:00, 84.64it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  23%|██▎       | 3/13 [00:00<00:00, 85.66it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  23%|██▎       | 3/13 [00:00<00:00, 85.11it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  31%|███       | 4/13 [00:00<00:00, 85.86it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  31%|███       | 4/13 [00:00<00:00, 85.48it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  38%|███▊      | 5/13 [00:00<00:00, 84.95it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  38%|███▊      | 5/13 [00:00<00:00, 84.65it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  46%|████▌     | 6/13 [00:00<00:00, 85.04it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  46%|████▌     | 6/13 [00:00<00:00, 84.79it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  54%|█████▍    | 7/13 [00:00<00:00, 85.22it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  54%|█████▍    | 7/13 [00:00<00:00, 84.99it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  62%|██████▏   | 8/13 [00:00<00:00, 85.25it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  62%|██████▏   | 8/13 [00:00<00:00, 85.06it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  69%|██████▉   | 9/13 [00:00<00:00, 85.25it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  69%|██████▉   | 9/13 [00:00<00:00, 85.08it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  77%|███████▋  | 10/13 [00:00<00:00, 84.72it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  77%|███████▋  | 10/13 [00:00<00:00, 84.54it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  85%|████████▍ | 11/13 [00:00<00:00, 84.90it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  85%|████████▍ | 11/13 [00:00<00:00, 84.77it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  92%|█████████▏| 12/13 [00:00<00:00, 84.99it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:  92%|█████████▏| 12/13 [00:00<00:00, 84.85it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 85.36it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 85.25it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 77.48it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 77.20it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 3:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]         
    Epoch 4:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:   8%|▊         | 1/13 [00:00<00:00, 87.03it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:   8%|▊         | 1/13 [00:00<00:00, 85.51it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  15%|█▌        | 2/13 [00:00<00:00, 85.07it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  15%|█▌        | 2/13 [00:00<00:00, 84.32it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  23%|██▎       | 3/13 [00:00<00:00, 85.03it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  23%|██▎       | 3/13 [00:00<00:00, 84.49it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  31%|███       | 4/13 [00:00<00:00, 84.55it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  31%|███       | 4/13 [00:00<00:00, 84.19it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  38%|███▊      | 5/13 [00:00<00:00, 84.50it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  38%|███▊      | 5/13 [00:00<00:00, 84.18it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  46%|████▌     | 6/13 [00:00<00:00, 84.67it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  46%|████▌     | 6/13 [00:00<00:00, 84.43it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  54%|█████▍    | 7/13 [00:00<00:00, 84.38it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  54%|█████▍    | 7/13 [00:00<00:00, 84.16it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  62%|██████▏   | 8/13 [00:00<00:00, 84.49it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  62%|██████▏   | 8/13 [00:00<00:00, 84.30it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  69%|██████▉   | 9/13 [00:00<00:00, 84.12it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  69%|██████▉   | 9/13 [00:00<00:00, 83.96it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  77%|███████▋  | 10/13 [00:00<00:00, 83.69it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  77%|███████▋  | 10/13 [00:00<00:00, 83.54it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  85%|████████▍ | 11/13 [00:00<00:00, 83.73it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  85%|████████▍ | 11/13 [00:00<00:00, 83.60it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  92%|█████████▏| 12/13 [00:00<00:00, 83.51it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:  92%|█████████▏| 12/13 [00:00<00:00, 83.38it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 83.68it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 83.54it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 76.07it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 75.80it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 4:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]         
    Epoch 5:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:   8%|▊         | 1/13 [00:00<00:00, 84.87it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:   8%|▊         | 1/13 [00:00<00:00, 83.42it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  15%|█▌        | 2/13 [00:00<00:00, 84.75it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  15%|█▌        | 2/13 [00:00<00:00, 84.01it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  23%|██▎       | 3/13 [00:00<00:00, 84.91it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  23%|██▎       | 3/13 [00:00<00:00, 84.42it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  31%|███       | 4/13 [00:00<00:00, 83.90it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  31%|███       | 4/13 [00:00<00:00, 83.51it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  38%|███▊      | 5/13 [00:00<00:00, 84.38it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  38%|███▊      | 5/13 [00:00<00:00, 84.08it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  46%|████▌     | 6/13 [00:00<00:00, 84.43it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  46%|████▌     | 6/13 [00:00<00:00, 84.16it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  54%|█████▍    | 7/13 [00:00<00:00, 84.46it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  54%|█████▍    | 7/13 [00:00<00:00, 84.25it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  62%|██████▏   | 8/13 [00:00<00:00, 84.30it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  62%|██████▏   | 8/13 [00:00<00:00, 84.12it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  69%|██████▉   | 9/13 [00:00<00:00, 83.97it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  69%|██████▉   | 9/13 [00:00<00:00, 83.79it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  77%|███████▋  | 10/13 [00:00<00:00, 83.93it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  77%|███████▋  | 10/13 [00:00<00:00, 83.79it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  85%|████████▍ | 11/13 [00:00<00:00, 84.14it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  85%|████████▍ | 11/13 [00:00<00:00, 84.00it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  92%|█████████▏| 12/13 [00:00<00:00, 84.13it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:  92%|█████████▏| 12/13 [00:00<00:00, 84.01it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 84.47it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 84.36it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 76.75it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 76.48it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 5:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]         
    Epoch 6:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:   8%|▊         | 1/13 [00:00<00:00, 81.48it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:   8%|▊         | 1/13 [00:00<00:00, 79.89it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  15%|█▌        | 2/13 [00:00<00:00, 83.24it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  15%|█▌        | 2/13 [00:00<00:00, 82.54it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  23%|██▎       | 3/13 [00:00<00:00, 84.07it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  23%|██▎       | 3/13 [00:00<00:00, 83.60it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  31%|███       | 4/13 [00:00<00:00, 84.49it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  31%|███       | 4/13 [00:00<00:00, 84.09it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  38%|███▊      | 5/13 [00:00<00:00, 84.88it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  38%|███▊      | 5/13 [00:00<00:00, 84.58it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  46%|████▌     | 6/13 [00:00<00:00, 84.42it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  46%|████▌     | 6/13 [00:00<00:00, 84.15it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  54%|█████▍    | 7/13 [00:00<00:00, 84.48it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  54%|█████▍    | 7/13 [00:00<00:00, 84.27it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  62%|██████▏   | 8/13 [00:00<00:00, 84.43it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  62%|██████▏   | 8/13 [00:00<00:00, 84.25it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  69%|██████▉   | 9/13 [00:00<00:00, 84.36it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  69%|██████▉   | 9/13 [00:00<00:00, 84.20it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  77%|███████▋  | 10/13 [00:00<00:00, 84.19it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  77%|███████▋  | 10/13 [00:00<00:00, 84.04it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  85%|████████▍ | 11/13 [00:00<00:00, 83.86it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  85%|████████▍ | 11/13 [00:00<00:00, 83.63it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  92%|█████████▏| 12/13 [00:00<00:00, 83.73it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:  92%|█████████▏| 12/13 [00:00<00:00, 83.60it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 83.90it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 83.73it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 75.19it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 74.91it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 6:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]         
    Epoch 7:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:   8%|▊         | 1/13 [00:00<00:00, 81.54it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:   8%|▊         | 1/13 [00:00<00:00, 80.20it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  15%|█▌        | 2/13 [00:00<00:00, 82.47it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  15%|█▌        | 2/13 [00:00<00:00, 81.78it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  23%|██▎       | 3/13 [00:00<00:00, 81.41it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  23%|██▎       | 3/13 [00:00<00:00, 80.93it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  31%|███       | 4/13 [00:00<00:00, 82.26it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  31%|███       | 4/13 [00:00<00:00, 81.71it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  38%|███▊      | 5/13 [00:00<00:00, 81.45it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  38%|███▊      | 5/13 [00:00<00:00, 81.14it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  46%|████▌     | 6/13 [00:00<00:00, 81.08it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  46%|████▌     | 6/13 [00:00<00:00, 80.81it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  54%|█████▍    | 7/13 [00:00<00:00, 81.46it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  54%|█████▍    | 7/13 [00:00<00:00, 81.25it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  62%|██████▏   | 8/13 [00:00<00:00, 81.06it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  62%|██████▏   | 8/13 [00:00<00:00, 80.87it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  69%|██████▉   | 9/13 [00:00<00:00, 81.09it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  69%|██████▉   | 9/13 [00:00<00:00, 80.92it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  77%|███████▋  | 10/13 [00:00<00:00, 81.32it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  77%|███████▋  | 10/13 [00:00<00:00, 81.17it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  85%|████████▍ | 11/13 [00:00<00:00, 81.39it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  85%|████████▍ | 11/13 [00:00<00:00, 81.25it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  92%|█████████▏| 12/13 [00:00<00:00, 81.33it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:  92%|█████████▏| 12/13 [00:00<00:00, 81.21it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 81.50it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 81.38it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 74.20it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 73.94it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 7:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]         
    Epoch 8:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:   8%|▊         | 1/13 [00:00<00:00, 82.18it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:   8%|▊         | 1/13 [00:00<00:00, 80.80it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  15%|█▌        | 2/13 [00:00<00:00, 83.42it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  15%|█▌        | 2/13 [00:00<00:00, 82.70it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  23%|██▎       | 3/13 [00:00<00:00, 83.33it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  23%|██▎       | 3/13 [00:00<00:00, 82.83it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  31%|███       | 4/13 [00:00<00:00, 83.45it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  31%|███       | 4/13 [00:00<00:00, 83.09it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  38%|███▊      | 5/13 [00:00<00:00, 83.21it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  38%|███▊      | 5/13 [00:00<00:00, 82.93it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  46%|████▌     | 6/13 [00:00<00:00, 83.53it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  46%|████▌     | 6/13 [00:00<00:00, 83.26it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  54%|█████▍    | 7/13 [00:00<00:00, 83.86it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  54%|█████▍    | 7/13 [00:00<00:00, 83.62it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  62%|██████▏   | 8/13 [00:00<00:00, 84.17it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  62%|██████▏   | 8/13 [00:00<00:00, 83.99it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  69%|██████▉   | 9/13 [00:00<00:00, 84.00it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  69%|██████▉   | 9/13 [00:00<00:00, 83.82it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  77%|███████▋  | 10/13 [00:00<00:00, 83.37it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  77%|███████▋  | 10/13 [00:00<00:00, 83.21it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  85%|████████▍ | 11/13 [00:00<00:00, 83.40it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  85%|████████▍ | 11/13 [00:00<00:00, 83.25it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  92%|█████████▏| 12/13 [00:00<00:00, 83.56it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:  92%|█████████▏| 12/13 [00:00<00:00, 83.43it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 83.95it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 83.84it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 76.26it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 75.99it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 8:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]         
    Epoch 9:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:   8%|▊         | 1/13 [00:00<00:00, 85.03it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:   8%|▊         | 1/13 [00:00<00:00, 83.36it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  15%|█▌        | 2/13 [00:00<00:00, 82.60it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  15%|█▌        | 2/13 [00:00<00:00, 81.89it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  23%|██▎       | 3/13 [00:00<00:00, 83.31it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  23%|██▎       | 3/13 [00:00<00:00, 82.83it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  31%|███       | 4/13 [00:00<00:00, 83.73it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  31%|███       | 4/13 [00:00<00:00, 83.32it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  38%|███▊      | 5/13 [00:00<00:00, 84.26it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  38%|███▊      | 5/13 [00:00<00:00, 83.97it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  46%|████▌     | 6/13 [00:00<00:00, 84.46it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  46%|████▌     | 6/13 [00:00<00:00, 84.22it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  54%|█████▍    | 7/13 [00:00<00:00, 84.07it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  54%|█████▍    | 7/13 [00:00<00:00, 83.86it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  62%|██████▏   | 8/13 [00:00<00:00, 84.16it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  62%|██████▏   | 8/13 [00:00<00:00, 83.98it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  69%|██████▉   | 9/13 [00:00<00:00, 84.47it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  69%|██████▉   | 9/13 [00:00<00:00, 84.31it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  77%|███████▋  | 10/13 [00:00<00:00, 84.70it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  77%|███████▋  | 10/13 [00:00<00:00, 84.55it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  85%|████████▍ | 11/13 [00:00<00:00, 84.86it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  85%|████████▍ | 11/13 [00:00<00:00, 84.73it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  92%|█████████▏| 12/13 [00:00<00:00, 84.70it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:  92%|█████████▏| 12/13 [00:00<00:00, 84.56it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 85.03it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 84.91it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 77.24it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 76.97it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 9:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]         
    Epoch 10:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:   8%|▊         | 1/13 [00:00<00:00, 84.95it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:   8%|▊         | 1/13 [00:00<00:00, 83.51it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  15%|█▌        | 2/13 [00:00<00:00, 85.60it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  15%|█▌        | 2/13 [00:00<00:00, 84.79it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  23%|██▎       | 3/13 [00:00<00:00, 85.58it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  23%|██▎       | 3/13 [00:00<00:00, 85.09it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  31%|███       | 4/13 [00:00<00:00, 84.84it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  31%|███       | 4/13 [00:00<00:00, 84.44it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  38%|███▊      | 5/13 [00:00<00:00, 85.17it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  38%|███▊      | 5/13 [00:00<00:00, 84.87it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  46%|████▌     | 6/13 [00:00<00:00, 85.29it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  46%|████▌     | 6/13 [00:00<00:00, 85.00it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  54%|█████▍    | 7/13 [00:00<00:00, 85.16it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  54%|█████▍    | 7/13 [00:00<00:00, 84.93it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  62%|██████▏   | 8/13 [00:00<00:00, 85.33it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  62%|██████▏   | 8/13 [00:00<00:00, 85.14it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  69%|██████▉   | 9/13 [00:00<00:00, 84.89it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  69%|██████▉   | 9/13 [00:00<00:00, 84.71it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  77%|███████▋  | 10/13 [00:00<00:00, 84.96it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  77%|███████▋  | 10/13 [00:00<00:00, 84.81it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  85%|████████▍ | 11/13 [00:00<00:00, 84.97it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  85%|████████▍ | 11/13 [00:00<00:00, 84.83it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  92%|█████████▏| 12/13 [00:00<00:00, 84.78it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:  92%|█████████▏| 12/13 [00:00<00:00, 84.65it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 84.92it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 84.76it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 76.93it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 76.64it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 10:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]         
    Epoch 11:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:   8%|▊         | 1/13 [00:00<00:00, 79.14it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:   8%|▊         | 1/13 [00:00<00:00, 77.76it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  15%|█▌        | 2/13 [00:00<00:00, 81.98it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  15%|█▌        | 2/13 [00:00<00:00, 81.30it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  23%|██▎       | 3/13 [00:00<00:00, 82.91it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  23%|██▎       | 3/13 [00:00<00:00, 82.39it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  31%|███       | 4/13 [00:00<00:00, 83.46it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  31%|███       | 4/13 [00:00<00:00, 83.08it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  38%|███▊      | 5/13 [00:00<00:00, 83.96it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  38%|███▊      | 5/13 [00:00<00:00, 83.68it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  46%|████▌     | 6/13 [00:00<00:00, 83.97it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  46%|████▌     | 6/13 [00:00<00:00, 83.73it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  54%|█████▍    | 7/13 [00:00<00:00, 83.36it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  54%|█████▍    | 7/13 [00:00<00:00, 83.10it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  62%|██████▏   | 8/13 [00:00<00:00, 83.37it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  62%|██████▏   | 8/13 [00:00<00:00, 83.18it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  69%|██████▉   | 9/13 [00:00<00:00, 83.52it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  69%|██████▉   | 9/13 [00:00<00:00, 83.36it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  77%|███████▋  | 10/13 [00:00<00:00, 83.47it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  77%|███████▋  | 10/13 [00:00<00:00, 83.32it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  85%|████████▍ | 11/13 [00:00<00:00, 83.59it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  85%|████████▍ | 11/13 [00:00<00:00, 83.46it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  92%|█████████▏| 12/13 [00:00<00:00, 83.69it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:  92%|█████████▏| 12/13 [00:00<00:00, 83.57it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 83.62it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 83.49it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 75.92it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 75.66it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 11:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]         
    Epoch 12:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:   8%|▊         | 1/13 [00:00<00:00, 82.64it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:   8%|▊         | 1/13 [00:00<00:00, 81.24it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  15%|█▌        | 2/13 [00:00<00:00, 83.92it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  15%|█▌        | 2/13 [00:00<00:00, 83.18it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  23%|██▎       | 3/13 [00:00<00:00, 83.79it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  23%|██▎       | 3/13 [00:00<00:00, 83.28it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  31%|███       | 4/13 [00:00<00:00, 83.77it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  31%|███       | 4/13 [00:00<00:00, 83.35it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  38%|███▊      | 5/13 [00:00<00:00, 83.01it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  38%|███▊      | 5/13 [00:00<00:00, 82.69it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  46%|████▌     | 6/13 [00:00<00:00, 83.46it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  46%|████▌     | 6/13 [00:00<00:00, 83.22it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  54%|█████▍    | 7/13 [00:00<00:00, 83.54it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  54%|█████▍    | 7/13 [00:00<00:00, 83.33it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  62%|██████▏   | 8/13 [00:00<00:00, 83.78it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  62%|██████▏   | 8/13 [00:00<00:00, 83.57it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  69%|██████▉   | 9/13 [00:00<00:00, 84.01it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  69%|██████▉   | 9/13 [00:00<00:00, 83.85it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  77%|███████▋  | 10/13 [00:00<00:00, 84.13it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  77%|███████▋  | 10/13 [00:00<00:00, 83.99it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  85%|████████▍ | 11/13 [00:00<00:00, 83.98it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  85%|████████▍ | 11/13 [00:00<00:00, 83.84it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  92%|█████████▏| 12/13 [00:00<00:00, 84.11it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:  92%|█████████▏| 12/13 [00:00<00:00, 83.98it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 84.53it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 84.42it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 76.79it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 76.51it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 12:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]         
    Epoch 13:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:   8%|▊         | 1/13 [00:00<00:00, 84.52it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:   8%|▊         | 1/13 [00:00<00:00, 83.09it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  15%|█▌        | 2/13 [00:00<00:00, 85.79it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  15%|█▌        | 2/13 [00:00<00:00, 85.05it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  23%|██▎       | 3/13 [00:00<00:00, 84.23it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  23%|██▎       | 3/13 [00:00<00:00, 83.73it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  31%|███       | 4/13 [00:00<00:00, 84.67it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  31%|███       | 4/13 [00:00<00:00, 84.26it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  38%|███▊      | 5/13 [00:00<00:00, 84.76it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  38%|███▊      | 5/13 [00:00<00:00, 84.43it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  46%|████▌     | 6/13 [00:00<00:00, 84.35it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  46%|████▌     | 6/13 [00:00<00:00, 84.07it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  54%|█████▍    | 7/13 [00:00<00:00, 84.32it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  54%|█████▍    | 7/13 [00:00<00:00, 84.09it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  62%|██████▏   | 8/13 [00:00<00:00, 84.33it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  62%|██████▏   | 8/13 [00:00<00:00, 84.14it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  69%|██████▉   | 9/13 [00:00<00:00, 83.99it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  69%|██████▉   | 9/13 [00:00<00:00, 83.79it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  77%|███████▋  | 10/13 [00:00<00:00, 84.05it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  77%|███████▋  | 10/13 [00:00<00:00, 83.90it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  85%|████████▍ | 11/13 [00:00<00:00, 84.25it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  85%|████████▍ | 11/13 [00:00<00:00, 84.12it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  92%|█████████▏| 12/13 [00:00<00:00, 84.34it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:  92%|█████████▏| 12/13 [00:00<00:00, 84.22it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 84.70it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 84.59it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 76.87it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 76.59it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 13:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]         
    Epoch 14:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:   8%|▊         | 1/13 [00:00<00:00, 82.46it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:   8%|▊         | 1/13 [00:00<00:00, 80.95it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  15%|█▌        | 2/13 [00:00<00:00, 80.96it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  15%|█▌        | 2/13 [00:00<00:00, 80.23it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  23%|██▎       | 3/13 [00:00<00:00, 82.30it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  23%|██▎       | 3/13 [00:00<00:00, 81.84it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  31%|███       | 4/13 [00:00<00:00, 83.28it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  31%|███       | 4/13 [00:00<00:00, 82.93it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  38%|███▊      | 5/13 [00:00<00:00, 84.01it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  38%|███▊      | 5/13 [00:00<00:00, 83.73it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  46%|████▌     | 6/13 [00:00<00:00, 83.40it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  46%|████▌     | 6/13 [00:00<00:00, 83.16it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  54%|█████▍    | 7/13 [00:00<00:00, 81.60it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  54%|█████▍    | 7/13 [00:00<00:00, 81.35it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  62%|██████▏   | 8/13 [00:00<00:00, 81.84it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  62%|██████▏   | 8/13 [00:00<00:00, 81.64it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  69%|██████▉   | 9/13 [00:00<00:00, 82.22it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  69%|██████▉   | 9/13 [00:00<00:00, 82.06it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  77%|███████▋  | 10/13 [00:00<00:00, 82.66it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  77%|███████▋  | 10/13 [00:00<00:00, 82.53it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  85%|████████▍ | 11/13 [00:00<00:00, 82.87it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  85%|████████▍ | 11/13 [00:00<00:00, 82.73it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  92%|█████████▏| 12/13 [00:00<00:00, 83.08it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:  92%|█████████▏| 12/13 [00:00<00:00, 82.97it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 83.22it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 83.10it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 75.73it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 75.46it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 14:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]         
    Epoch 15:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:   8%|▊         | 1/13 [00:00<00:00, 85.03it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:   8%|▊         | 1/13 [00:00<00:00, 83.43it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  15%|█▌        | 2/13 [00:00<00:00, 85.02it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  15%|█▌        | 2/13 [00:00<00:00, 84.29it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  23%|██▎       | 3/13 [00:00<00:00, 85.34it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  23%|██▎       | 3/13 [00:00<00:00, 84.85it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  31%|███       | 4/13 [00:00<00:00, 85.74it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  31%|███       | 4/13 [00:00<00:00, 85.36it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  38%|███▊      | 5/13 [00:00<00:00, 84.64it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  38%|███▊      | 5/13 [00:00<00:00, 84.31it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  46%|████▌     | 6/13 [00:00<00:00, 84.73it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  46%|████▌     | 6/13 [00:00<00:00, 84.46it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  54%|█████▍    | 7/13 [00:00<00:00, 84.82it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  54%|█████▍    | 7/13 [00:00<00:00, 84.61it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  62%|██████▏   | 8/13 [00:00<00:00, 85.03it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  62%|██████▏   | 8/13 [00:00<00:00, 84.82it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  69%|██████▉   | 9/13 [00:00<00:00, 85.12it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  69%|██████▉   | 9/13 [00:00<00:00, 84.93it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  77%|███████▋  | 10/13 [00:00<00:00, 85.15it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  77%|███████▋  | 10/13 [00:00<00:00, 85.00it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  85%|████████▍ | 11/13 [00:00<00:00, 84.58it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  85%|████████▍ | 11/13 [00:00<00:00, 84.41it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  92%|█████████▏| 12/13 [00:00<00:00, 84.44it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15:  92%|█████████▏| 12/13 [00:00<00:00, 84.31it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 84.71it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 84.59it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 76.66it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 76.38it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 76.08it/s, v_num=ld_1, val_loss=0.693, train_loss=0.693]
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
         Validate metric           DataLoader 0
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
            AUROC_val                   0.5
          Accuracy_val          0.4300000071525574
            val_loss            0.6931471824645996
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────

    Training: |          | 0/? [00:00<?, ?it/s]
    Training:   0%|          | 0/13 [00:00<?, ?it/s]
    Epoch 0:   0%|          | 0/13 [00:00<?, ?it/s] 
    Epoch 0:   8%|▊         | 1/13 [00:00<00:00, 48.44it/s]
    Epoch 0:   8%|▊         | 1/13 [00:00<00:00, 47.65it/s, v_num=ld_2]
    Epoch 0:  15%|█▌        | 2/13 [00:00<00:00, 52.74it/s, v_num=ld_2]
    Epoch 0:  15%|█▌        | 2/13 [00:00<00:00, 52.33it/s, v_num=ld_2]
    Epoch 0:  23%|██▎       | 3/13 [00:00<00:00, 54.16it/s, v_num=ld_2]
    Epoch 0:  23%|██▎       | 3/13 [00:00<00:00, 53.87it/s, v_num=ld_2]
    Epoch 0:  31%|███       | 4/13 [00:00<00:00, 55.89it/s, v_num=ld_2]
    Epoch 0:  31%|███       | 4/13 [00:00<00:00, 55.74it/s, v_num=ld_2]
    Epoch 0:  38%|███▊      | 5/13 [00:00<00:00, 60.01it/s, v_num=ld_2]
    Epoch 0:  38%|███▊      | 5/13 [00:00<00:00, 59.87it/s, v_num=ld_2]
    Epoch 0:  46%|████▌     | 6/13 [00:00<00:00, 62.64it/s, v_num=ld_2]
    Epoch 0:  46%|████▌     | 6/13 [00:00<00:00, 62.49it/s, v_num=ld_2]
    Epoch 0:  54%|█████▍    | 7/13 [00:00<00:00, 65.14it/s, v_num=ld_2]
    Epoch 0:  54%|█████▍    | 7/13 [00:00<00:00, 65.01it/s, v_num=ld_2]
    Epoch 0:  62%|██████▏   | 8/13 [00:00<00:00, 67.16it/s, v_num=ld_2]
    Epoch 0:  62%|██████▏   | 8/13 [00:00<00:00, 67.06it/s, v_num=ld_2]
    Epoch 0:  69%|██████▉   | 9/13 [00:00<00:00, 68.91it/s, v_num=ld_2]
    Epoch 0:  69%|██████▉   | 9/13 [00:00<00:00, 68.80it/s, v_num=ld_2]
    Epoch 0:  77%|███████▋  | 10/13 [00:00<00:00, 70.35it/s, v_num=ld_2]
    Epoch 0:  77%|███████▋  | 10/13 [00:00<00:00, 70.25it/s, v_num=ld_2]
    Epoch 0:  85%|████████▍ | 11/13 [00:00<00:00, 71.61it/s, v_num=ld_2]
    Epoch 0:  85%|████████▍ | 11/13 [00:00<00:00, 71.52it/s, v_num=ld_2]
    Epoch 0:  92%|█████████▏| 12/13 [00:00<00:00, 72.43it/s, v_num=ld_2]
    Epoch 0:  92%|█████████▏| 12/13 [00:00<00:00, 72.33it/s, v_num=ld_2]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 73.53it/s, v_num=ld_2]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 73.44it/s, v_num=ld_2]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 67.47it/s, v_num=ld_2, val_loss=0.588]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 67.26it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 0:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]         
    Epoch 1:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:   8%|▊         | 1/13 [00:00<00:00, 85.90it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:   8%|▊         | 1/13 [00:00<00:00, 84.29it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  15%|█▌        | 2/13 [00:00<00:00, 86.44it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  15%|█▌        | 2/13 [00:00<00:00, 85.69it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  23%|██▎       | 3/13 [00:00<00:00, 85.86it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  23%|██▎       | 3/13 [00:00<00:00, 85.35it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  31%|███       | 4/13 [00:00<00:00, 86.11it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  31%|███       | 4/13 [00:00<00:00, 85.69it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  38%|███▊      | 5/13 [00:00<00:00, 86.20it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  38%|███▊      | 5/13 [00:00<00:00, 85.89it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  46%|████▌     | 6/13 [00:00<00:00, 86.27it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  46%|████▌     | 6/13 [00:00<00:00, 85.99it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  54%|█████▍    | 7/13 [00:00<00:00, 85.97it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  54%|█████▍    | 7/13 [00:00<00:00, 85.75it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  62%|██████▏   | 8/13 [00:00<00:00, 85.67it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  62%|██████▏   | 8/13 [00:00<00:00, 85.49it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  69%|██████▉   | 9/13 [00:00<00:00, 85.14it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  69%|██████▉   | 9/13 [00:00<00:00, 84.87it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  77%|███████▋  | 10/13 [00:00<00:00, 84.93it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  77%|███████▋  | 10/13 [00:00<00:00, 84.78it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  85%|████████▍ | 11/13 [00:00<00:00, 84.85it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  85%|████████▍ | 11/13 [00:00<00:00, 84.70it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  92%|█████████▏| 12/13 [00:00<00:00, 84.83it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1:  92%|█████████▏| 12/13 [00:00<00:00, 84.69it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 85.11it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 85.00it/s, v_num=ld_2, val_loss=0.588, train_loss=0.666]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 77.16it/s, v_num=ld_2, val_loss=0.559, train_loss=0.666]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 76.88it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 1:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]         
    Epoch 2:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:   8%|▊         | 1/13 [00:00<00:00, 80.42it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:   8%|▊         | 1/13 [00:00<00:00, 79.09it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  15%|█▌        | 2/13 [00:00<00:00, 82.35it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  15%|█▌        | 2/13 [00:00<00:00, 81.67it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  23%|██▎       | 3/13 [00:00<00:00, 83.45it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  23%|██▎       | 3/13 [00:00<00:00, 82.97it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  31%|███       | 4/13 [00:00<00:00, 83.81it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  31%|███       | 4/13 [00:00<00:00, 83.41it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  38%|███▊      | 5/13 [00:00<00:00, 84.10it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  38%|███▊      | 5/13 [00:00<00:00, 83.81it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  46%|████▌     | 6/13 [00:00<00:00, 84.45it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  46%|████▌     | 6/13 [00:00<00:00, 84.21it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  54%|█████▍    | 7/13 [00:00<00:00, 84.02it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  54%|█████▍    | 7/13 [00:00<00:00, 83.79it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  62%|██████▏   | 8/13 [00:00<00:00, 83.86it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  62%|██████▏   | 8/13 [00:00<00:00, 83.68it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  69%|██████▉   | 9/13 [00:00<00:00, 84.03it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  69%|██████▉   | 9/13 [00:00<00:00, 83.87it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  77%|███████▋  | 10/13 [00:00<00:00, 84.10it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  77%|███████▋  | 10/13 [00:00<00:00, 83.94it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  85%|████████▍ | 11/13 [00:00<00:00, 84.05it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  85%|████████▍ | 11/13 [00:00<00:00, 83.91it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  92%|█████████▏| 12/13 [00:00<00:00, 84.29it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2:  92%|█████████▏| 12/13 [00:00<00:00, 84.17it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 84.17it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 84.05it/s, v_num=ld_2, val_loss=0.559, train_loss=0.583]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 76.56it/s, v_num=ld_2, val_loss=0.610, train_loss=0.583]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 76.27it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 2:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]         
    Epoch 3:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:   8%|▊         | 1/13 [00:00<00:00, 85.73it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:   8%|▊         | 1/13 [00:00<00:00, 84.14it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  15%|█▌        | 2/13 [00:00<00:00, 86.20it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  15%|█▌        | 2/13 [00:00<00:00, 85.46it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  23%|██▎       | 3/13 [00:00<00:00, 86.49it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  23%|██▎       | 3/13 [00:00<00:00, 85.91it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  31%|███       | 4/13 [00:00<00:00, 86.38it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  31%|███       | 4/13 [00:00<00:00, 86.00it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  38%|███▊      | 5/13 [00:00<00:00, 85.46it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  38%|███▊      | 5/13 [00:00<00:00, 85.12it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  46%|████▌     | 6/13 [00:00<00:00, 85.57it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  46%|████▌     | 6/13 [00:00<00:00, 85.32it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  54%|█████▍    | 7/13 [00:00<00:00, 85.75it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  54%|█████▍    | 7/13 [00:00<00:00, 85.53it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  62%|██████▏   | 8/13 [00:00<00:00, 85.87it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  62%|██████▏   | 8/13 [00:00<00:00, 85.68it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  69%|██████▉   | 9/13 [00:00<00:00, 86.06it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  69%|██████▉   | 9/13 [00:00<00:00, 85.89it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  77%|███████▋  | 10/13 [00:00<00:00, 86.07it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  77%|███████▋  | 10/13 [00:00<00:00, 85.91it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  85%|████████▍ | 11/13 [00:00<00:00, 85.67it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  85%|████████▍ | 11/13 [00:00<00:00, 85.52it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  92%|█████████▏| 12/13 [00:00<00:00, 85.68it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3:  92%|█████████▏| 12/13 [00:00<00:00, 85.56it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 85.96it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 85.85it/s, v_num=ld_2, val_loss=0.610, train_loss=0.570]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 78.04it/s, v_num=ld_2, val_loss=0.572, train_loss=0.570]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 77.75it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 3:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]         
    Epoch 4:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:   8%|▊         | 1/13 [00:00<00:00, 86.84it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:   8%|▊         | 1/13 [00:00<00:00, 85.34it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  15%|█▌        | 2/13 [00:00<00:00, 85.70it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  15%|█▌        | 2/13 [00:00<00:00, 84.95it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  23%|██▎       | 3/13 [00:00<00:00, 84.61it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  23%|██▎       | 3/13 [00:00<00:00, 84.09it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  31%|███       | 4/13 [00:00<00:00, 85.10it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  31%|███       | 4/13 [00:00<00:00, 84.69it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  38%|███▊      | 5/13 [00:00<00:00, 85.37it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  38%|███▊      | 5/13 [00:00<00:00, 85.07it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  46%|████▌     | 6/13 [00:00<00:00, 85.79it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  46%|████▌     | 6/13 [00:00<00:00, 85.52it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  54%|█████▍    | 7/13 [00:00<00:00, 86.01it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  54%|█████▍    | 7/13 [00:00<00:00, 85.80it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  62%|██████▏   | 8/13 [00:00<00:00, 86.20it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  62%|██████▏   | 8/13 [00:00<00:00, 86.01it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  69%|██████▉   | 9/13 [00:00<00:00, 85.77it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  69%|██████▉   | 9/13 [00:00<00:00, 85.57it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  77%|███████▋  | 10/13 [00:00<00:00, 85.77it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  77%|███████▋  | 10/13 [00:00<00:00, 85.62it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  85%|████████▍ | 11/13 [00:00<00:00, 85.83it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  85%|████████▍ | 11/13 [00:00<00:00, 85.69it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  92%|█████████▏| 12/13 [00:00<00:00, 85.82it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4:  92%|█████████▏| 12/13 [00:00<00:00, 85.68it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 86.14it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 86.00it/s, v_num=ld_2, val_loss=0.572, train_loss=0.560]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 78.17it/s, v_num=ld_2, val_loss=0.606, train_loss=0.560]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 77.90it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 4:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]         
    Epoch 5:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:   8%|▊         | 1/13 [00:00<00:00, 83.16it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:   8%|▊         | 1/13 [00:00<00:00, 81.65it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  15%|█▌        | 2/13 [00:00<00:00, 84.54it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  15%|█▌        | 2/13 [00:00<00:00, 83.74it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  23%|██▎       | 3/13 [00:00<00:00, 85.51it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  23%|██▎       | 3/13 [00:00<00:00, 85.01it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  31%|███       | 4/13 [00:00<00:00, 85.74it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  31%|███       | 4/13 [00:00<00:00, 85.37it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  38%|███▊      | 5/13 [00:00<00:00, 86.15it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  38%|███▊      | 5/13 [00:00<00:00, 85.85it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  46%|████▌     | 6/13 [00:00<00:00, 86.28it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  46%|████▌     | 6/13 [00:00<00:00, 86.02it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  54%|█████▍    | 7/13 [00:00<00:00, 85.74it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  54%|█████▍    | 7/13 [00:00<00:00, 85.51it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  62%|██████▏   | 8/13 [00:00<00:00, 85.75it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  62%|██████▏   | 8/13 [00:00<00:00, 85.56it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  69%|██████▉   | 9/13 [00:00<00:00, 85.69it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  69%|██████▉   | 9/13 [00:00<00:00, 85.52it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  77%|███████▋  | 10/13 [00:00<00:00, 85.77it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  77%|███████▋  | 10/13 [00:00<00:00, 85.63it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  85%|████████▍ | 11/13 [00:00<00:00, 85.81it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  85%|████████▍ | 11/13 [00:00<00:00, 85.68it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  92%|█████████▏| 12/13 [00:00<00:00, 85.66it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5:  92%|█████████▏| 12/13 [00:00<00:00, 85.53it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 85.21it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 85.09it/s, v_num=ld_2, val_loss=0.606, train_loss=0.550]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 77.24it/s, v_num=ld_2, val_loss=0.589, train_loss=0.550]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 76.94it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 5:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]         
    Epoch 6:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:   8%|▊         | 1/13 [00:00<00:00, 81.66it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:   8%|▊         | 1/13 [00:00<00:00, 80.29it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  15%|█▌        | 2/13 [00:00<00:00, 82.93it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  15%|█▌        | 2/13 [00:00<00:00, 82.15it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  23%|██▎       | 3/13 [00:00<00:00, 83.69it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  23%|██▎       | 3/13 [00:00<00:00, 83.16it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  31%|███       | 4/13 [00:00<00:00, 84.03it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  31%|███       | 4/13 [00:00<00:00, 83.67it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  38%|███▊      | 5/13 [00:00<00:00, 83.67it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  38%|███▊      | 5/13 [00:00<00:00, 83.34it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  46%|████▌     | 6/13 [00:00<00:00, 83.41it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  46%|████▌     | 6/13 [00:00<00:00, 83.17it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  54%|█████▍    | 7/13 [00:00<00:00, 83.82it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  54%|█████▍    | 7/13 [00:00<00:00, 83.49it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  62%|██████▏   | 8/13 [00:00<00:00, 83.89it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  62%|██████▏   | 8/13 [00:00<00:00, 83.70it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  69%|██████▉   | 9/13 [00:00<00:00, 84.03it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  69%|██████▉   | 9/13 [00:00<00:00, 83.86it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  77%|███████▋  | 10/13 [00:00<00:00, 84.01it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  77%|███████▋  | 10/13 [00:00<00:00, 83.87it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  85%|████████▍ | 11/13 [00:00<00:00, 83.87it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  85%|████████▍ | 11/13 [00:00<00:00, 83.73it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  92%|█████████▏| 12/13 [00:00<00:00, 84.08it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6:  92%|█████████▏| 12/13 [00:00<00:00, 83.95it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 84.62it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 84.50it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 76.91it/s, v_num=ld_2, val_loss=0.589, train_loss=0.576]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 76.65it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 6:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]         
    Epoch 7:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:   8%|▊         | 1/13 [00:00<00:00, 86.71it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:   8%|▊         | 1/13 [00:00<00:00, 85.06it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  15%|█▌        | 2/13 [00:00<00:00, 87.03it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  15%|█▌        | 2/13 [00:00<00:00, 86.27it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  23%|██▎       | 3/13 [00:00<00:00, 85.48it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  23%|██▎       | 3/13 [00:00<00:00, 84.94it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  31%|███       | 4/13 [00:00<00:00, 85.88it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  31%|███       | 4/13 [00:00<00:00, 85.48it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  38%|███▊      | 5/13 [00:00<00:00, 86.11it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  38%|███▊      | 5/13 [00:00<00:00, 85.81it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  46%|████▌     | 6/13 [00:00<00:00, 86.33it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  46%|████▌     | 6/13 [00:00<00:00, 86.04it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  54%|█████▍    | 7/13 [00:00<00:00, 86.53it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  54%|█████▍    | 7/13 [00:00<00:00, 86.31it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  62%|██████▏   | 8/13 [00:00<00:00, 86.53it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  62%|██████▏   | 8/13 [00:00<00:00, 86.32it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  69%|██████▉   | 9/13 [00:00<00:00, 86.12it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  69%|██████▉   | 9/13 [00:00<00:00, 85.92it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  77%|███████▋  | 10/13 [00:00<00:00, 86.10it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  77%|███████▋  | 10/13 [00:00<00:00, 85.95it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  85%|████████▍ | 11/13 [00:00<00:00, 86.19it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  85%|████████▍ | 11/13 [00:00<00:00, 86.03it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  92%|█████████▏| 12/13 [00:00<00:00, 86.17it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7:  92%|█████████▏| 12/13 [00:00<00:00, 86.05it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 86.53it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 86.41it/s, v_num=ld_2, val_loss=0.589, train_loss=0.565]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 78.49it/s, v_num=ld_2, val_loss=0.559, train_loss=0.565]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 78.20it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 7:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]         
    Epoch 8:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:   8%|▊         | 1/13 [00:00<00:00, 81.64it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:   8%|▊         | 1/13 [00:00<00:00, 80.18it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  15%|█▌        | 2/13 [00:00<00:00, 83.76it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  15%|█▌        | 2/13 [00:00<00:00, 83.05it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  23%|██▎       | 3/13 [00:00<00:00, 84.58it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  23%|██▎       | 3/13 [00:00<00:00, 84.10it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  31%|███       | 4/13 [00:00<00:00, 84.60it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  31%|███       | 4/13 [00:00<00:00, 84.23it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  38%|███▊      | 5/13 [00:00<00:00, 84.96it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  38%|███▊      | 5/13 [00:00<00:00, 84.66it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  46%|████▌     | 6/13 [00:00<00:00, 85.10it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  46%|████▌     | 6/13 [00:00<00:00, 84.85it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  54%|█████▍    | 7/13 [00:00<00:00, 84.54it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  54%|█████▍    | 7/13 [00:00<00:00, 84.31it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  62%|██████▏   | 8/13 [00:00<00:00, 84.60it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  62%|██████▏   | 8/13 [00:00<00:00, 84.40it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  69%|██████▉   | 9/13 [00:00<00:00, 84.72it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  69%|██████▉   | 9/13 [00:00<00:00, 84.55it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  77%|███████▋  | 10/13 [00:00<00:00, 84.85it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  77%|███████▋  | 10/13 [00:00<00:00, 84.70it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  85%|████████▍ | 11/13 [00:00<00:00, 84.93it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  85%|████████▍ | 11/13 [00:00<00:00, 84.80it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  92%|█████████▏| 12/13 [00:00<00:00, 85.17it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8:  92%|█████████▏| 12/13 [00:00<00:00, 85.05it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 85.34it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 85.22it/s, v_num=ld_2, val_loss=0.559, train_loss=0.547]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 77.54it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 77.27it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 8:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]         
    Epoch 9:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:   8%|▊         | 1/13 [00:00<00:00, 85.92it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:   8%|▊         | 1/13 [00:00<00:00, 84.23it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  15%|█▌        | 2/13 [00:00<00:00, 85.91it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  15%|█▌        | 2/13 [00:00<00:00, 85.16it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  23%|██▎       | 3/13 [00:00<00:00, 86.32it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  23%|██▎       | 3/13 [00:00<00:00, 85.77it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  31%|███       | 4/13 [00:00<00:00, 86.63it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  31%|███       | 4/13 [00:00<00:00, 86.25it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  38%|███▊      | 5/13 [00:00<00:00, 85.93it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  38%|███▊      | 5/13 [00:00<00:00, 85.62it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  46%|████▌     | 6/13 [00:00<00:00, 85.98it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  46%|████▌     | 6/13 [00:00<00:00, 85.71it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  54%|█████▍    | 7/13 [00:00<00:00, 86.01it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  54%|█████▍    | 7/13 [00:00<00:00, 85.80it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  62%|██████▏   | 8/13 [00:00<00:00, 85.94it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  62%|██████▏   | 8/13 [00:00<00:00, 85.75it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  69%|██████▉   | 9/13 [00:00<00:00, 86.00it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  69%|██████▉   | 9/13 [00:00<00:00, 85.81it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  77%|███████▋  | 10/13 [00:00<00:00, 86.00it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  77%|███████▋  | 10/13 [00:00<00:00, 85.85it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  85%|████████▍ | 11/13 [00:00<00:00, 85.65it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  85%|████████▍ | 11/13 [00:00<00:00, 85.50it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  92%|█████████▏| 12/13 [00:00<00:00, 85.64it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9:  92%|█████████▏| 12/13 [00:00<00:00, 85.51it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 86.07it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 85.95it/s, v_num=ld_2, val_loss=0.549, train_loss=0.547]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 78.17it/s, v_num=ld_2, val_loss=0.545, train_loss=0.547]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 77.89it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 9:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]         
    Epoch 10:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:   8%|▊         | 1/13 [00:00<00:00, 85.73it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:   8%|▊         | 1/13 [00:00<00:00, 84.25it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  15%|█▌        | 2/13 [00:00<00:00, 86.02it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  15%|█▌        | 2/13 [00:00<00:00, 85.20it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  23%|██▎       | 3/13 [00:00<00:00, 84.93it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  23%|██▎       | 3/13 [00:00<00:00, 84.39it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  31%|███       | 4/13 [00:00<00:00, 85.29it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  31%|███       | 4/13 [00:00<00:00, 84.92it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  38%|███▊      | 5/13 [00:00<00:00, 85.52it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  38%|███▊      | 5/13 [00:00<00:00, 85.23it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  46%|████▌     | 6/13 [00:00<00:00, 85.25it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  46%|████▌     | 6/13 [00:00<00:00, 84.97it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  54%|█████▍    | 7/13 [00:00<00:00, 85.35it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  54%|█████▍    | 7/13 [00:00<00:00, 85.14it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  62%|██████▏   | 8/13 [00:00<00:00, 85.52it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  62%|██████▏   | 8/13 [00:00<00:00, 85.33it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  69%|██████▉   | 9/13 [00:00<00:00, 85.22it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  69%|██████▉   | 9/13 [00:00<00:00, 85.03it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  77%|███████▋  | 10/13 [00:00<00:00, 85.36it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  77%|███████▋  | 10/13 [00:00<00:00, 85.20it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  85%|████████▍ | 11/13 [00:00<00:00, 85.41it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  85%|████████▍ | 11/13 [00:00<00:00, 85.28it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  92%|█████████▏| 12/13 [00:00<00:00, 85.51it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10:  92%|█████████▏| 12/13 [00:00<00:00, 85.39it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 85.86it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 85.75it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 75.57it/s, v_num=ld_2, val_loss=0.545, train_loss=0.535]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 75.05it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 10:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]         
    Epoch 11:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:   8%|▊         | 1/13 [00:00<00:00, 43.94it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:   8%|▊         | 1/13 [00:00<00:00, 42.90it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  15%|█▌        | 2/13 [00:00<00:00, 47.84it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  15%|█▌        | 2/13 [00:00<00:00, 47.53it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  23%|██▎       | 3/13 [00:00<00:00, 54.92it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  23%|██▎       | 3/13 [00:00<00:00, 54.68it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  31%|███       | 4/13 [00:00<00:00, 59.07it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  31%|███       | 4/13 [00:00<00:00, 58.86it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  38%|███▊      | 5/13 [00:00<00:00, 62.88it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  38%|███▊      | 5/13 [00:00<00:00, 62.72it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  46%|████▌     | 6/13 [00:00<00:00, 65.63it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  46%|████▌     | 6/13 [00:00<00:00, 65.48it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  54%|█████▍    | 7/13 [00:00<00:00, 67.24it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  54%|█████▍    | 7/13 [00:00<00:00, 67.10it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  62%|██████▏   | 8/13 [00:00<00:00, 69.10it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  62%|██████▏   | 8/13 [00:00<00:00, 68.97it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  69%|██████▉   | 9/13 [00:00<00:00, 70.59it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  69%|██████▉   | 9/13 [00:00<00:00, 70.48it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  77%|███████▋  | 10/13 [00:00<00:00, 71.80it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  77%|███████▋  | 10/13 [00:00<00:00, 71.69it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  85%|████████▍ | 11/13 [00:00<00:00, 72.88it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  85%|████████▍ | 11/13 [00:00<00:00, 72.78it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  92%|█████████▏| 12/13 [00:00<00:00, 73.49it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11:  92%|█████████▏| 12/13 [00:00<00:00, 73.40it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 74.22it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 74.13it/s, v_num=ld_2, val_loss=0.545, train_loss=0.528]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 68.04it/s, v_num=ld_2, val_loss=0.566, train_loss=0.528]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 67.83it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 11:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]         
    Epoch 12:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:   8%|▊         | 1/13 [00:00<00:00, 80.92it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:   8%|▊         | 1/13 [00:00<00:00, 79.60it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  15%|█▌        | 2/13 [00:00<00:00, 82.90it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  15%|█▌        | 2/13 [00:00<00:00, 82.21it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  23%|██▎       | 3/13 [00:00<00:00, 83.94it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  23%|██▎       | 3/13 [00:00<00:00, 83.47it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  31%|███       | 4/13 [00:00<00:00, 83.79it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  31%|███       | 4/13 [00:00<00:00, 83.42it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  38%|███▊      | 5/13 [00:00<00:00, 83.57it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  38%|███▊      | 5/13 [00:00<00:00, 83.25it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  46%|████▌     | 6/13 [00:00<00:00, 83.96it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  46%|████▌     | 6/13 [00:00<00:00, 83.70it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  54%|█████▍    | 7/13 [00:00<00:00, 84.27it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  54%|█████▍    | 7/13 [00:00<00:00, 84.06it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  62%|██████▏   | 8/13 [00:00<00:00, 84.67it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  62%|██████▏   | 8/13 [00:00<00:00, 84.47it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  69%|██████▉   | 9/13 [00:00<00:00, 84.85it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  69%|██████▉   | 9/13 [00:00<00:00, 84.69it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  77%|███████▋  | 10/13 [00:00<00:00, 84.19it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  77%|███████▋  | 10/13 [00:00<00:00, 84.05it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  85%|████████▍ | 11/13 [00:00<00:00, 84.14it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  85%|████████▍ | 11/13 [00:00<00:00, 83.99it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  92%|█████████▏| 12/13 [00:00<00:00, 84.33it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12:  92%|█████████▏| 12/13 [00:00<00:00, 84.21it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 84.52it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 84.40it/s, v_num=ld_2, val_loss=0.566, train_loss=0.527]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 76.87it/s, v_num=ld_2, val_loss=0.571, train_loss=0.527]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 76.59it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 12:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]         
    Epoch 13:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:   8%|▊         | 1/13 [00:00<00:00, 85.62it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:   8%|▊         | 1/13 [00:00<00:00, 84.17it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  15%|█▌        | 2/13 [00:00<00:00, 84.64it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  15%|█▌        | 2/13 [00:00<00:00, 83.91it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  23%|██▎       | 3/13 [00:00<00:00, 82.89it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  23%|██▎       | 3/13 [00:00<00:00, 82.33it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  31%|███       | 4/13 [00:00<00:00, 82.14it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  31%|███       | 4/13 [00:00<00:00, 81.80it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  38%|███▊      | 5/13 [00:00<00:00, 82.25it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  38%|███▊      | 5/13 [00:00<00:00, 81.98it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  46%|████▌     | 6/13 [00:00<00:00, 81.71it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  46%|████▌     | 6/13 [00:00<00:00, 81.45it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  54%|█████▍    | 7/13 [00:00<00:00, 81.82it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  54%|█████▍    | 7/13 [00:00<00:00, 81.62it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  62%|██████▏   | 8/13 [00:00<00:00, 81.90it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  62%|██████▏   | 8/13 [00:00<00:00, 81.73it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  69%|██████▉   | 9/13 [00:00<00:00, 81.72it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  69%|██████▉   | 9/13 [00:00<00:00, 81.53it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  77%|███████▋  | 10/13 [00:00<00:00, 81.97it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  77%|███████▋  | 10/13 [00:00<00:00, 81.83it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  85%|████████▍ | 11/13 [00:00<00:00, 82.05it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  85%|████████▍ | 11/13 [00:00<00:00, 81.90it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  92%|█████████▏| 12/13 [00:00<00:00, 82.49it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13:  92%|█████████▏| 12/13 [00:00<00:00, 82.37it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 82.97it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 82.86it/s, v_num=ld_2, val_loss=0.571, train_loss=0.524]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 75.50it/s, v_num=ld_2, val_loss=0.599, train_loss=0.524]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 75.24it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 13:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]         
    Epoch 14:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:   8%|▊         | 1/13 [00:00<00:00, 81.76it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:   8%|▊         | 1/13 [00:00<00:00, 80.35it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  15%|█▌        | 2/13 [00:00<00:00, 82.98it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  15%|█▌        | 2/13 [00:00<00:00, 82.28it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  23%|██▎       | 3/13 [00:00<00:00, 83.22it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  23%|██▎       | 3/13 [00:00<00:00, 82.75it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  31%|███       | 4/13 [00:00<00:00, 84.13it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  31%|███       | 4/13 [00:00<00:00, 83.77it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  38%|███▊      | 5/13 [00:00<00:00, 84.08it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  38%|███▊      | 5/13 [00:00<00:00, 83.79it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  46%|████▌     | 6/13 [00:00<00:00, 83.96it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  46%|████▌     | 6/13 [00:00<00:00, 83.72it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  54%|█████▍    | 7/13 [00:00<00:00, 83.51it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  54%|█████▍    | 7/13 [00:00<00:00, 83.27it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  62%|██████▏   | 8/13 [00:00<00:00, 83.77it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  62%|██████▏   | 8/13 [00:00<00:00, 83.59it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  69%|██████▉   | 9/13 [00:00<00:00, 83.76it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  69%|██████▉   | 9/13 [00:00<00:00, 83.60it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  77%|███████▋  | 10/13 [00:00<00:00, 83.86it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  77%|███████▋  | 10/13 [00:00<00:00, 83.72it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  85%|████████▍ | 11/13 [00:00<00:00, 83.21it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  85%|████████▍ | 11/13 [00:00<00:00, 83.08it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  92%|█████████▏| 12/13 [00:00<00:00, 82.99it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14:  92%|█████████▏| 12/13 [00:00<00:00, 82.88it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 83.04it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 82.93it/s, v_num=ld_2, val_loss=0.599, train_loss=0.525]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 75.69it/s, v_num=ld_2, val_loss=0.555, train_loss=0.525]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 75.43it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 14:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]         
    Epoch 15:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:   8%|▊         | 1/13 [00:00<00:00, 82.13it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:   8%|▊         | 1/13 [00:00<00:00, 80.79it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  15%|█▌        | 2/13 [00:00<00:00, 83.08it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  15%|█▌        | 2/13 [00:00<00:00, 82.39it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  23%|██▎       | 3/13 [00:00<00:00, 84.10it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  23%|██▎       | 3/13 [00:00<00:00, 83.58it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  31%|███       | 4/13 [00:00<00:00, 84.49it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  31%|███       | 4/13 [00:00<00:00, 84.12it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  38%|███▊      | 5/13 [00:00<00:00, 82.40it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  38%|███▊      | 5/13 [00:00<00:00, 82.06it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  46%|████▌     | 6/13 [00:00<00:00, 82.67it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  46%|████▌     | 6/13 [00:00<00:00, 82.43it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  54%|█████▍    | 7/13 [00:00<00:00, 82.74it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  54%|█████▍    | 7/13 [00:00<00:00, 82.52it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  62%|██████▏   | 8/13 [00:00<00:00, 80.66it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  62%|██████▏   | 8/13 [00:00<00:00, 80.49it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  69%|██████▉   | 9/13 [00:00<00:00, 81.07it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  69%|██████▉   | 9/13 [00:00<00:00, 80.92it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  77%|███████▋  | 10/13 [00:00<00:00, 81.33it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  77%|███████▋  | 10/13 [00:00<00:00, 81.20it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  85%|████████▍ | 11/13 [00:00<00:00, 80.73it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  85%|████████▍ | 11/13 [00:00<00:00, 80.59it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  92%|█████████▏| 12/13 [00:00<00:00, 80.14it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15:  92%|█████████▏| 12/13 [00:00<00:00, 80.02it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 80.75it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 80.65it/s, v_num=ld_2, val_loss=0.555, train_loss=0.522]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 73.65it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 73.39it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 15:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]         
    Epoch 16:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:   8%|▊         | 1/13 [00:00<00:00, 85.76it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:   8%|▊         | 1/13 [00:00<00:00, 84.30it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  15%|█▌        | 2/13 [00:00<00:00, 84.92it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  15%|█▌        | 2/13 [00:00<00:00, 84.18it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  23%|██▎       | 3/13 [00:00<00:00, 81.86it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  23%|██▎       | 3/13 [00:00<00:00, 81.36it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  31%|███       | 4/13 [00:00<00:00, 80.42it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  31%|███       | 4/13 [00:00<00:00, 80.09it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  38%|███▊      | 5/13 [00:00<00:00, 80.88it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  38%|███▊      | 5/13 [00:00<00:00, 80.61it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  46%|████▌     | 6/13 [00:00<00:00, 81.11it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  46%|████▌     | 6/13 [00:00<00:00, 80.87it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  54%|█████▍    | 7/13 [00:00<00:00, 81.44it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  54%|█████▍    | 7/13 [00:00<00:00, 81.21it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  62%|██████▏   | 8/13 [00:00<00:00, 81.61it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  62%|██████▏   | 8/13 [00:00<00:00, 81.42it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  69%|██████▉   | 9/13 [00:00<00:00, 81.31it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  69%|██████▉   | 9/13 [00:00<00:00, 81.15it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  77%|███████▋  | 10/13 [00:00<00:00, 81.56it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  77%|███████▋  | 10/13 [00:00<00:00, 81.43it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  85%|████████▍ | 11/13 [00:00<00:00, 81.78it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  85%|████████▍ | 11/13 [00:00<00:00, 81.66it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  92%|█████████▏| 12/13 [00:00<00:00, 81.86it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16:  92%|█████████▏| 12/13 [00:00<00:00, 81.74it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 82.48it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 82.37it/s, v_num=ld_2, val_loss=0.550, train_loss=0.522]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 75.08it/s, v_num=ld_2, val_loss=0.556, train_loss=0.522]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 74.83it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 16:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]         
    Epoch 17:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:   8%|▊         | 1/13 [00:00<00:00, 79.47it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:   8%|▊         | 1/13 [00:00<00:00, 77.92it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  15%|█▌        | 2/13 [00:00<00:00, 78.35it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  15%|█▌        | 2/13 [00:00<00:00, 77.74it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  23%|██▎       | 3/13 [00:00<00:00, 80.82it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  23%|██▎       | 3/13 [00:00<00:00, 80.38it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  31%|███       | 4/13 [00:00<00:00, 82.20it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  31%|███       | 4/13 [00:00<00:00, 81.82it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  38%|███▊      | 5/13 [00:00<00:00, 83.13it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  38%|███▊      | 5/13 [00:00<00:00, 82.86it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  46%|████▌     | 6/13 [00:00<00:00, 83.23it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  46%|████▌     | 6/13 [00:00<00:00, 83.00it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  54%|█████▍    | 7/13 [00:00<00:00, 82.80it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  54%|█████▍    | 7/13 [00:00<00:00, 82.47it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  62%|██████▏   | 8/13 [00:00<00:00, 82.95it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  62%|██████▏   | 8/13 [00:00<00:00, 82.76it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  69%|██████▉   | 9/13 [00:00<00:00, 83.37it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  69%|██████▉   | 9/13 [00:00<00:00, 83.22it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  77%|███████▋  | 10/13 [00:00<00:00, 83.63it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  77%|███████▋  | 10/13 [00:00<00:00, 83.47it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  85%|████████▍ | 11/13 [00:00<00:00, 83.78it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  85%|████████▍ | 11/13 [00:00<00:00, 83.65it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  92%|█████████▏| 12/13 [00:00<00:00, 83.87it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17:  92%|█████████▏| 12/13 [00:00<00:00, 83.75it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 83.97it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 83.85it/s, v_num=ld_2, val_loss=0.556, train_loss=0.523]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 76.06it/s, v_num=ld_2, val_loss=0.559, train_loss=0.523]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 75.80it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 17:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]         
    Epoch 18:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:   8%|▊         | 1/13 [00:00<00:00, 83.99it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:   8%|▊         | 1/13 [00:00<00:00, 82.56it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  15%|█▌        | 2/13 [00:00<00:00, 83.63it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  15%|█▌        | 2/13 [00:00<00:00, 82.93it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  23%|██▎       | 3/13 [00:00<00:00, 82.98it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  23%|██▎       | 3/13 [00:00<00:00, 82.51it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  31%|███       | 4/13 [00:00<00:00, 83.47it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  31%|███       | 4/13 [00:00<00:00, 83.11it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  38%|███▊      | 5/13 [00:00<00:00, 81.82it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  38%|███▊      | 5/13 [00:00<00:00, 81.53it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  46%|████▌     | 6/13 [00:00<00:00, 81.13it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  46%|████▌     | 6/13 [00:00<00:00, 80.90it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  54%|█████▍    | 7/13 [00:00<00:00, 81.84it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  54%|█████▍    | 7/13 [00:00<00:00, 81.62it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  62%|██████▏   | 8/13 [00:00<00:00, 82.18it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  62%|██████▏   | 8/13 [00:00<00:00, 82.01it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  69%|██████▉   | 9/13 [00:00<00:00, 82.62it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  69%|██████▉   | 9/13 [00:00<00:00, 82.46it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  77%|███████▋  | 10/13 [00:00<00:00, 82.88it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  77%|███████▋  | 10/13 [00:00<00:00, 82.74it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  85%|████████▍ | 11/13 [00:00<00:00, 82.74it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  85%|████████▍ | 11/13 [00:00<00:00, 82.60it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  92%|█████████▏| 12/13 [00:00<00:00, 82.93it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18:  92%|█████████▏| 12/13 [00:00<00:00, 82.81it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 83.50it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 83.39it/s, v_num=ld_2, val_loss=0.559, train_loss=0.536]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 75.95it/s, v_num=ld_2, val_loss=0.565, train_loss=0.536]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 75.68it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 18:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]         
    Epoch 19:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:   8%|▊         | 1/13 [00:00<00:00, 84.63it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:   8%|▊         | 1/13 [00:00<00:00, 83.20it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  15%|█▌        | 2/13 [00:00<00:00, 84.53it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  15%|█▌        | 2/13 [00:00<00:00, 83.80it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  23%|██▎       | 3/13 [00:00<00:00, 81.79it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  23%|██▎       | 3/13 [00:00<00:00, 81.29it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  31%|███       | 4/13 [00:00<00:00, 82.57it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  31%|███       | 4/13 [00:00<00:00, 82.22it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  38%|███▊      | 5/13 [00:00<00:00, 82.32it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  38%|███▊      | 5/13 [00:00<00:00, 82.04it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  46%|████▌     | 6/13 [00:00<00:00, 82.42it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  46%|████▌     | 6/13 [00:00<00:00, 82.19it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  54%|█████▍    | 7/13 [00:00<00:00, 83.11it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  54%|█████▍    | 7/13 [00:00<00:00, 82.89it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  62%|██████▏   | 8/13 [00:00<00:00, 83.52it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  62%|██████▏   | 8/13 [00:00<00:00, 83.34it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  69%|██████▉   | 9/13 [00:00<00:00, 83.45it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  69%|██████▉   | 9/13 [00:00<00:00, 83.27it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  77%|███████▋  | 10/13 [00:00<00:00, 83.49it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  77%|███████▋  | 10/13 [00:00<00:00, 83.35it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  85%|████████▍ | 11/13 [00:00<00:00, 83.43it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  85%|████████▍ | 11/13 [00:00<00:00, 83.30it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  92%|█████████▏| 12/13 [00:00<00:00, 83.51it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19:  92%|█████████▏| 12/13 [00:00<00:00, 83.39it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 84.03it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 83.92it/s, v_num=ld_2, val_loss=0.565, train_loss=0.546]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 76.46it/s, v_num=ld_2, val_loss=0.567, train_loss=0.546]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 76.18it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 19:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]         
    Epoch 20:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:   8%|▊         | 1/13 [00:00<00:00, 81.73it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:   8%|▊         | 1/13 [00:00<00:00, 80.28it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  15%|█▌        | 2/13 [00:00<00:00, 82.55it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  15%|█▌        | 2/13 [00:00<00:00, 81.86it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  23%|██▎       | 3/13 [00:00<00:00, 83.17it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  23%|██▎       | 3/13 [00:00<00:00, 82.70it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  31%|███       | 4/13 [00:00<00:00, 83.70it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  31%|███       | 4/13 [00:00<00:00, 83.34it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  38%|███▊      | 5/13 [00:00<00:00, 84.16it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  38%|███▊      | 5/13 [00:00<00:00, 83.84it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  46%|████▌     | 6/13 [00:00<00:00, 84.09it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  46%|████▌     | 6/13 [00:00<00:00, 83.85it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  54%|█████▍    | 7/13 [00:00<00:00, 83.56it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  54%|█████▍    | 7/13 [00:00<00:00, 83.34it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  62%|██████▏   | 8/13 [00:00<00:00, 83.78it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  62%|██████▏   | 8/13 [00:00<00:00, 83.60it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  69%|██████▉   | 9/13 [00:00<00:00, 83.82it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  69%|██████▉   | 9/13 [00:00<00:00, 83.66it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  77%|███████▋  | 10/13 [00:00<00:00, 83.51it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  77%|███████▋  | 10/13 [00:00<00:00, 83.36it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  85%|████████▍ | 11/13 [00:00<00:00, 83.83it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  85%|████████▍ | 11/13 [00:00<00:00, 83.70it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  92%|█████████▏| 12/13 [00:00<00:00, 83.60it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20:  92%|█████████▏| 12/13 [00:00<00:00, 83.48it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 83.84it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 83.72it/s, v_num=ld_2, val_loss=0.567, train_loss=0.525]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 76.28it/s, v_num=ld_2, val_loss=0.612, train_loss=0.525]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 76.02it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 20:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]         
    Epoch 21:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:   8%|▊         | 1/13 [00:00<00:00, 84.40it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:   8%|▊         | 1/13 [00:00<00:00, 82.98it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  15%|█▌        | 2/13 [00:00<00:00, 85.38it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  15%|█▌        | 2/13 [00:00<00:00, 84.63it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  23%|██▎       | 3/13 [00:00<00:00, 83.92it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  23%|██▎       | 3/13 [00:00<00:00, 83.44it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  31%|███       | 4/13 [00:00<00:00, 83.21it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  31%|███       | 4/13 [00:00<00:00, 82.86it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  38%|███▊      | 5/13 [00:00<00:00, 81.98it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  38%|███▊      | 5/13 [00:00<00:00, 81.70it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  46%|████▌     | 6/13 [00:00<00:00, 82.52it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  46%|████▌     | 6/13 [00:00<00:00, 82.29it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  54%|█████▍    | 7/13 [00:00<00:00, 82.55it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  54%|█████▍    | 7/13 [00:00<00:00, 82.35it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  62%|██████▏   | 8/13 [00:00<00:00, 82.51it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  62%|██████▏   | 8/13 [00:00<00:00, 82.34it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  69%|██████▉   | 9/13 [00:00<00:00, 82.64it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  69%|██████▉   | 9/13 [00:00<00:00, 82.48it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  77%|███████▋  | 10/13 [00:00<00:00, 82.95it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  77%|███████▋  | 10/13 [00:00<00:00, 82.81it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  85%|████████▍ | 11/13 [00:00<00:00, 82.84it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  85%|████████▍ | 11/13 [00:00<00:00, 82.70it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  92%|█████████▏| 12/13 [00:00<00:00, 82.95it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21:  92%|█████████▏| 12/13 [00:00<00:00, 82.82it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 83.37it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 83.26it/s, v_num=ld_2, val_loss=0.612, train_loss=0.533]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 75.93it/s, v_num=ld_2, val_loss=0.606, train_loss=0.533]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 75.66it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 21:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]         
    Epoch 22:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:   8%|▊         | 1/13 [00:00<00:00, 85.27it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:   8%|▊         | 1/13 [00:00<00:00, 83.81it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  15%|█▌        | 2/13 [00:00<00:00, 84.01it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  15%|█▌        | 2/13 [00:00<00:00, 83.22it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  23%|██▎       | 3/13 [00:00<00:00, 82.46it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  23%|██▎       | 3/13 [00:00<00:00, 81.96it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  31%|███       | 4/13 [00:00<00:00, 82.09it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  31%|███       | 4/13 [00:00<00:00, 81.73it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  38%|███▊      | 5/13 [00:00<00:00, 82.35it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  38%|███▊      | 5/13 [00:00<00:00, 82.06it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  46%|████▌     | 6/13 [00:00<00:00, 82.62it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  46%|████▌     | 6/13 [00:00<00:00, 82.39it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  54%|█████▍    | 7/13 [00:00<00:00, 82.00it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  54%|█████▍    | 7/13 [00:00<00:00, 81.80it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  62%|██████▏   | 8/13 [00:00<00:00, 81.50it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  62%|██████▏   | 8/13 [00:00<00:00, 81.33it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  69%|██████▉   | 9/13 [00:00<00:00, 81.59it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  69%|██████▉   | 9/13 [00:00<00:00, 81.42it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  77%|███████▋  | 10/13 [00:00<00:00, 82.04it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  77%|███████▋  | 10/13 [00:00<00:00, 81.89it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  85%|████████▍ | 11/13 [00:00<00:00, 81.49it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  85%|████████▍ | 11/13 [00:00<00:00, 81.36it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  92%|█████████▏| 12/13 [00:00<00:00, 81.18it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22:  92%|█████████▏| 12/13 [00:00<00:00, 81.06it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 81.45it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 81.35it/s, v_num=ld_2, val_loss=0.606, train_loss=0.549]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 74.15it/s, v_num=ld_2, val_loss=0.581, train_loss=0.549]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 73.80it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 22:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]         
    Epoch 23:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:   8%|▊         | 1/13 [00:00<00:00, 79.40it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:   8%|▊         | 1/13 [00:00<00:00, 78.01it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  15%|█▌        | 2/13 [00:00<00:00, 78.41it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  15%|█▌        | 2/13 [00:00<00:00, 77.77it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  23%|██▎       | 3/13 [00:00<00:00, 80.69it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  23%|██▎       | 3/13 [00:00<00:00, 80.21it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  31%|███       | 4/13 [00:00<00:00, 80.37it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  31%|███       | 4/13 [00:00<00:00, 80.04it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  38%|███▊      | 5/13 [00:00<00:00, 78.98it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  38%|███▊      | 5/13 [00:00<00:00, 78.72it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  46%|████▌     | 6/13 [00:00<00:00, 79.68it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  46%|████▌     | 6/13 [00:00<00:00, 79.46it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  54%|█████▍    | 7/13 [00:00<00:00, 79.86it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  54%|█████▍    | 7/13 [00:00<00:00, 79.66it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  62%|██████▏   | 8/13 [00:00<00:00, 80.52it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  62%|██████▏   | 8/13 [00:00<00:00, 80.36it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  69%|██████▉   | 9/13 [00:00<00:00, 80.50it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  69%|██████▉   | 9/13 [00:00<00:00, 80.35it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  77%|███████▋  | 10/13 [00:00<00:00, 80.92it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  77%|███████▋  | 10/13 [00:00<00:00, 80.78it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  85%|████████▍ | 11/13 [00:00<00:00, 80.89it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  85%|████████▍ | 11/13 [00:00<00:00, 80.75it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  92%|█████████▏| 12/13 [00:00<00:00, 80.49it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23:  92%|█████████▏| 12/13 [00:00<00:00, 80.37it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 80.91it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 80.79it/s, v_num=ld_2, val_loss=0.581, train_loss=0.561]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 73.81it/s, v_num=ld_2, val_loss=0.593, train_loss=0.561]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 73.55it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 23:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]         
    Epoch 24:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:   8%|▊         | 1/13 [00:00<00:00, 83.92it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:   8%|▊         | 1/13 [00:00<00:00, 82.51it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  15%|█▌        | 2/13 [00:00<00:00, 85.19it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  15%|█▌        | 2/13 [00:00<00:00, 84.44it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  23%|██▎       | 3/13 [00:00<00:00, 85.50it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  23%|██▎       | 3/13 [00:00<00:00, 85.00it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  31%|███       | 4/13 [00:00<00:00, 84.91it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  31%|███       | 4/13 [00:00<00:00, 84.55it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  38%|███▊      | 5/13 [00:00<00:00, 84.21it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  38%|███▊      | 5/13 [00:00<00:00, 83.91it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  46%|████▌     | 6/13 [00:00<00:00, 83.50it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  46%|████▌     | 6/13 [00:00<00:00, 83.26it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  54%|█████▍    | 7/13 [00:00<00:00, 83.70it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  54%|█████▍    | 7/13 [00:00<00:00, 83.48it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  62%|██████▏   | 8/13 [00:00<00:00, 83.72it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  62%|██████▏   | 8/13 [00:00<00:00, 83.55it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  69%|██████▉   | 9/13 [00:00<00:00, 84.10it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  69%|██████▉   | 9/13 [00:00<00:00, 83.94it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  77%|███████▋  | 10/13 [00:00<00:00, 84.01it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  77%|███████▋  | 10/13 [00:00<00:00, 83.87it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  85%|████████▍ | 11/13 [00:00<00:00, 83.61it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  85%|████████▍ | 11/13 [00:00<00:00, 83.45it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  92%|█████████▏| 12/13 [00:00<00:00, 82.65it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24:  92%|█████████▏| 12/13 [00:00<00:00, 82.53it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 82.96it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 82.84it/s, v_num=ld_2, val_loss=0.593, train_loss=0.544]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 75.25it/s, v_num=ld_2, val_loss=0.574, train_loss=0.544]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 74.97it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 24:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]         
    Epoch 25:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:   8%|▊         | 1/13 [00:00<00:00, 71.81it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:   8%|▊         | 1/13 [00:00<00:00, 70.77it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  15%|█▌        | 2/13 [00:00<00:00, 73.34it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  15%|█▌        | 2/13 [00:00<00:00, 72.79it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  23%|██▎       | 3/13 [00:00<00:00, 74.06it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  23%|██▎       | 3/13 [00:00<00:00, 73.62it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  31%|███       | 4/13 [00:00<00:00, 74.97it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  31%|███       | 4/13 [00:00<00:00, 74.68it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  38%|███▊      | 5/13 [00:00<00:00, 76.74it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  38%|███▊      | 5/13 [00:00<00:00, 76.50it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  46%|████▌     | 6/13 [00:00<00:00, 76.76it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  46%|████▌     | 6/13 [00:00<00:00, 76.56it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  54%|█████▍    | 7/13 [00:00<00:00, 77.85it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  54%|█████▍    | 7/13 [00:00<00:00, 77.67it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  62%|██████▏   | 8/13 [00:00<00:00, 78.83it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  62%|██████▏   | 8/13 [00:00<00:00, 78.68it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  69%|██████▉   | 9/13 [00:00<00:00, 78.07it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  69%|██████▉   | 9/13 [00:00<00:00, 77.92it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  77%|███████▋  | 10/13 [00:00<00:00, 77.64it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  77%|███████▋  | 10/13 [00:00<00:00, 77.49it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  85%|████████▍ | 11/13 [00:00<00:00, 77.96it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  85%|████████▍ | 11/13 [00:00<00:00, 77.85it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  92%|█████████▏| 12/13 [00:00<00:00, 78.16it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25:  92%|█████████▏| 12/13 [00:00<00:00, 78.05it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 78.89it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 78.79it/s, v_num=ld_2, val_loss=0.574, train_loss=0.534]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 72.14it/s, v_num=ld_2, val_loss=0.586, train_loss=0.534]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 71.89it/s, v_num=ld_2, val_loss=0.586, train_loss=0.544]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 71.63it/s, v_num=ld_2, val_loss=0.586, train_loss=0.544]
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
         Validate metric           DataLoader 0
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
            AUROC_val           0.8121175169944763
          Accuracy_val          0.7699999809265137
            val_loss            0.5859994292259216
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────

    Training: |          | 0/? [00:00<?, ?it/s]
    Training:   0%|          | 0/13 [00:00<?, ?it/s]
    Epoch 0:   0%|          | 0/13 [00:00<?, ?it/s] 
    Epoch 0:   8%|▊         | 1/13 [00:00<00:00, 53.30it/s]
    Epoch 0:   8%|▊         | 1/13 [00:00<00:00, 52.45it/s, v_num=ld_3]
    Epoch 0:  15%|█▌        | 2/13 [00:00<00:00, 56.27it/s, v_num=ld_3]
    Epoch 0:  15%|█▌        | 2/13 [00:00<00:00, 55.78it/s, v_num=ld_3]
    Epoch 0:  23%|██▎       | 3/13 [00:00<00:00, 57.56it/s, v_num=ld_3]
    Epoch 0:  23%|██▎       | 3/13 [00:00<00:00, 57.26it/s, v_num=ld_3]
    Epoch 0:  31%|███       | 4/13 [00:00<00:00, 58.20it/s, v_num=ld_3]
    Epoch 0:  31%|███       | 4/13 [00:00<00:00, 57.97it/s, v_num=ld_3]
    Epoch 0:  38%|███▊      | 5/13 [00:00<00:00, 61.92it/s, v_num=ld_3]
    Epoch 0:  38%|███▊      | 5/13 [00:00<00:00, 61.78it/s, v_num=ld_3]
    Epoch 0:  46%|████▌     | 6/13 [00:00<00:00, 65.15it/s, v_num=ld_3]
    Epoch 0:  46%|████▌     | 6/13 [00:00<00:00, 65.02it/s, v_num=ld_3]
    Epoch 0:  54%|█████▍    | 7/13 [00:00<00:00, 66.95it/s, v_num=ld_3]
    Epoch 0:  54%|█████▍    | 7/13 [00:00<00:00, 66.82it/s, v_num=ld_3]
    Epoch 0:  62%|██████▏   | 8/13 [00:00<00:00, 68.85it/s, v_num=ld_3]
    Epoch 0:  62%|██████▏   | 8/13 [00:00<00:00, 68.73it/s, v_num=ld_3]
    Epoch 0:  69%|██████▉   | 9/13 [00:00<00:00, 70.56it/s, v_num=ld_3]
    Epoch 0:  69%|██████▉   | 9/13 [00:00<00:00, 70.43it/s, v_num=ld_3]
    Epoch 0:  77%|███████▋  | 10/13 [00:00<00:00, 71.97it/s, v_num=ld_3]
    Epoch 0:  77%|███████▋  | 10/13 [00:00<00:00, 71.88it/s, v_num=ld_3]
    Epoch 0:  85%|████████▍ | 11/13 [00:00<00:00, 73.16it/s, v_num=ld_3]
    Epoch 0:  85%|████████▍ | 11/13 [00:00<00:00, 73.06it/s, v_num=ld_3]
    Epoch 0:  92%|█████████▏| 12/13 [00:00<00:00, 74.15it/s, v_num=ld_3]
    Epoch 0:  92%|█████████▏| 12/13 [00:00<00:00, 74.07it/s, v_num=ld_3]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 75.02it/s, v_num=ld_3]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 74.94it/s, v_num=ld_3]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 68.74it/s, v_num=ld_3, val_loss=0.660]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 68.53it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 0:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]         
    Epoch 1:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:   8%|▊         | 1/13 [00:00<00:00, 87.67it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:   8%|▊         | 1/13 [00:00<00:00, 86.14it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  15%|█▌        | 2/13 [00:00<00:00, 87.48it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  15%|█▌        | 2/13 [00:00<00:00, 86.71it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  23%|██▎       | 3/13 [00:00<00:00, 86.77it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  23%|██▎       | 3/13 [00:00<00:00, 86.22it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  31%|███       | 4/13 [00:00<00:00, 86.87it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  31%|███       | 4/13 [00:00<00:00, 86.45it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  38%|███▊      | 5/13 [00:00<00:00, 87.09it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  38%|███▊      | 5/13 [00:00<00:00, 86.79it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  46%|████▌     | 6/13 [00:00<00:00, 87.24it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  46%|████▌     | 6/13 [00:00<00:00, 86.98it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  54%|█████▍    | 7/13 [00:00<00:00, 87.30it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  54%|█████▍    | 7/13 [00:00<00:00, 87.08it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  62%|██████▏   | 8/13 [00:00<00:00, 87.33it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  62%|██████▏   | 8/13 [00:00<00:00, 87.14it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  69%|██████▉   | 9/13 [00:00<00:00, 87.02it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  69%|██████▉   | 9/13 [00:00<00:00, 86.85it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  77%|███████▋  | 10/13 [00:00<00:00, 87.10it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  77%|███████▋  | 10/13 [00:00<00:00, 86.95it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  85%|████████▍ | 11/13 [00:00<00:00, 87.20it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  85%|████████▍ | 11/13 [00:00<00:00, 87.06it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  92%|█████████▏| 12/13 [00:00<00:00, 87.25it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1:  92%|█████████▏| 12/13 [00:00<00:00, 87.12it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 87.55it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 87.43it/s, v_num=ld_3, val_loss=0.660, train_loss=0.688]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 79.42it/s, v_num=ld_3, val_loss=0.602, train_loss=0.688]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 79.13it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 1:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]         
    Epoch 2:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:   8%|▊         | 1/13 [00:00<00:00, 83.33it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:   8%|▊         | 1/13 [00:00<00:00, 81.55it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  15%|█▌        | 2/13 [00:00<00:00, 85.26it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  15%|█▌        | 2/13 [00:00<00:00, 84.53it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  23%|██▎       | 3/13 [00:00<00:00, 86.40it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  23%|██▎       | 3/13 [00:00<00:00, 85.90it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  31%|███       | 4/13 [00:00<00:00, 86.18it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  31%|███       | 4/13 [00:00<00:00, 85.81it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  38%|███▊      | 5/13 [00:00<00:00, 85.53it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  38%|███▊      | 5/13 [00:00<00:00, 85.23it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  46%|████▌     | 6/13 [00:00<00:00, 86.00it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  46%|████▌     | 6/13 [00:00<00:00, 85.75it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  54%|█████▍    | 7/13 [00:00<00:00, 85.65it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  54%|█████▍    | 7/13 [00:00<00:00, 85.42it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  62%|██████▏   | 8/13 [00:00<00:00, 85.84it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  62%|██████▏   | 8/13 [00:00<00:00, 85.63it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  69%|██████▉   | 9/13 [00:00<00:00, 85.89it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  69%|██████▉   | 9/13 [00:00<00:00, 85.72it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  77%|███████▋  | 10/13 [00:00<00:00, 85.96it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  77%|███████▋  | 10/13 [00:00<00:00, 85.81it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  85%|████████▍ | 11/13 [00:00<00:00, 86.12it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  85%|████████▍ | 11/13 [00:00<00:00, 85.99it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  92%|█████████▏| 12/13 [00:00<00:00, 86.23it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2:  92%|█████████▏| 12/13 [00:00<00:00, 86.09it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 86.02it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 85.88it/s, v_num=ld_3, val_loss=0.602, train_loss=0.595]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 77.87it/s, v_num=ld_3, val_loss=0.593, train_loss=0.595]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 77.58it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 2:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]         
    Epoch 3:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:   8%|▊         | 1/13 [00:00<00:00, 84.96it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:   8%|▊         | 1/13 [00:00<00:00, 83.22it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  15%|█▌        | 2/13 [00:00<00:00, 85.98it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  15%|█▌        | 2/13 [00:00<00:00, 85.23it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  23%|██▎       | 3/13 [00:00<00:00, 86.46it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  23%|██▎       | 3/13 [00:00<00:00, 85.95it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  31%|███       | 4/13 [00:00<00:00, 86.58it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  31%|███       | 4/13 [00:00<00:00, 86.20it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  38%|███▊      | 5/13 [00:00<00:00, 86.04it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  38%|███▊      | 5/13 [00:00<00:00, 85.71it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  46%|████▌     | 6/13 [00:00<00:00, 86.20it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  46%|████▌     | 6/13 [00:00<00:00, 85.95it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  54%|█████▍    | 7/13 [00:00<00:00, 86.34it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  54%|█████▍    | 7/13 [00:00<00:00, 86.12it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  62%|██████▏   | 8/13 [00:00<00:00, 86.35it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  62%|██████▏   | 8/13 [00:00<00:00, 86.16it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  69%|██████▉   | 9/13 [00:00<00:00, 86.40it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  69%|██████▉   | 9/13 [00:00<00:00, 86.23it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  77%|███████▋  | 10/13 [00:00<00:00, 86.54it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  77%|███████▋  | 10/13 [00:00<00:00, 86.38it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  85%|████████▍ | 11/13 [00:00<00:00, 86.29it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  85%|████████▍ | 11/13 [00:00<00:00, 86.15it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  92%|█████████▏| 12/13 [00:00<00:00, 86.37it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3:  92%|█████████▏| 12/13 [00:00<00:00, 86.23it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 86.66it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 86.54it/s, v_num=ld_3, val_loss=0.593, train_loss=0.566]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 78.66it/s, v_num=ld_3, val_loss=0.682, train_loss=0.566]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 78.39it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 3:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]         
    Epoch 4:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:   8%|▊         | 1/13 [00:00<00:00, 85.52it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:   8%|▊         | 1/13 [00:00<00:00, 84.07it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  15%|█▌        | 2/13 [00:00<00:00, 86.07it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  15%|█▌        | 2/13 [00:00<00:00, 85.32it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  23%|██▎       | 3/13 [00:00<00:00, 84.74it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  23%|██▎       | 3/13 [00:00<00:00, 84.15it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  31%|███       | 4/13 [00:00<00:00, 85.14it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  31%|███       | 4/13 [00:00<00:00, 84.78it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  38%|███▊      | 5/13 [00:00<00:00, 85.21it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  38%|███▊      | 5/13 [00:00<00:00, 84.92it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  46%|████▌     | 6/13 [00:00<00:00, 85.27it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  46%|████▌     | 6/13 [00:00<00:00, 85.00it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  54%|█████▍    | 7/13 [00:00<00:00, 85.41it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  54%|█████▍    | 7/13 [00:00<00:00, 85.20it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  62%|██████▏   | 8/13 [00:00<00:00, 85.77it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  62%|██████▏   | 8/13 [00:00<00:00, 85.57it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  69%|██████▉   | 9/13 [00:00<00:00, 85.46it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  69%|██████▉   | 9/13 [00:00<00:00, 85.25it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  77%|███████▋  | 10/13 [00:00<00:00, 85.33it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  77%|███████▋  | 10/13 [00:00<00:00, 85.17it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  85%|████████▍ | 11/13 [00:00<00:00, 85.47it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  85%|████████▍ | 11/13 [00:00<00:00, 85.34it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  92%|█████████▏| 12/13 [00:00<00:00, 85.63it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4:  92%|█████████▏| 12/13 [00:00<00:00, 85.50it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 85.99it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 85.88it/s, v_num=ld_3, val_loss=0.682, train_loss=0.548]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 78.13it/s, v_num=ld_3, val_loss=0.609, train_loss=0.548]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 77.85it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 4:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]         
    Epoch 5:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:   8%|▊         | 1/13 [00:00<00:00, 84.37it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:   8%|▊         | 1/13 [00:00<00:00, 82.66it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  15%|█▌        | 2/13 [00:00<00:00, 85.54it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  15%|█▌        | 2/13 [00:00<00:00, 84.80it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  23%|██▎       | 3/13 [00:00<00:00, 86.24it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  23%|██▎       | 3/13 [00:00<00:00, 85.69it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  31%|███       | 4/13 [00:00<00:00, 86.33it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  31%|███       | 4/13 [00:00<00:00, 85.95it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  38%|███▊      | 5/13 [00:00<00:00, 86.46it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  38%|███▊      | 5/13 [00:00<00:00, 86.12it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  46%|████▌     | 6/13 [00:00<00:00, 86.79it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  46%|████▌     | 6/13 [00:00<00:00, 86.53it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  54%|█████▍    | 7/13 [00:00<00:00, 86.29it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  54%|█████▍    | 7/13 [00:00<00:00, 86.07it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  62%|██████▏   | 8/13 [00:00<00:00, 86.22it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  62%|██████▏   | 8/13 [00:00<00:00, 86.02it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  69%|██████▉   | 9/13 [00:00<00:00, 86.40it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  69%|██████▉   | 9/13 [00:00<00:00, 86.23it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  77%|███████▋  | 10/13 [00:00<00:00, 86.56it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  77%|███████▋  | 10/13 [00:00<00:00, 86.41it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  85%|████████▍ | 11/13 [00:00<00:00, 86.53it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  85%|████████▍ | 11/13 [00:00<00:00, 86.39it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  92%|█████████▏| 12/13 [00:00<00:00, 86.61it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5:  92%|█████████▏| 12/13 [00:00<00:00, 86.49it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 86.75it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 86.62it/s, v_num=ld_3, val_loss=0.609, train_loss=0.572]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 78.60it/s, v_num=ld_3, val_loss=0.581, train_loss=0.572]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 78.31it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 5:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]         
    Epoch 6:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:   8%|▊         | 1/13 [00:00<00:00, 86.91it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:   8%|▊         | 1/13 [00:00<00:00, 85.32it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  15%|█▌        | 2/13 [00:00<00:00, 87.25it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  15%|█▌        | 2/13 [00:00<00:00, 86.49it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  23%|██▎       | 3/13 [00:00<00:00, 87.00it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  23%|██▎       | 3/13 [00:00<00:00, 86.49it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  31%|███       | 4/13 [00:00<00:00, 87.18it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  31%|███       | 4/13 [00:00<00:00, 86.80it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  38%|███▊      | 5/13 [00:00<00:00, 86.49it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  38%|███▊      | 5/13 [00:00<00:00, 86.17it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  46%|████▌     | 6/13 [00:00<00:00, 86.80it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  46%|████▌     | 6/13 [00:00<00:00, 86.51it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  54%|█████▍    | 7/13 [00:00<00:00, 86.71it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  54%|█████▍    | 7/13 [00:00<00:00, 86.49it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  62%|██████▏   | 8/13 [00:00<00:00, 86.65it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  62%|██████▏   | 8/13 [00:00<00:00, 86.45it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  69%|██████▉   | 9/13 [00:00<00:00, 86.69it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  69%|██████▉   | 9/13 [00:00<00:00, 86.52it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  77%|███████▋  | 10/13 [00:00<00:00, 86.74it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  77%|███████▋  | 10/13 [00:00<00:00, 86.57it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  85%|████████▍ | 11/13 [00:00<00:00, 86.43it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  85%|████████▍ | 11/13 [00:00<00:00, 86.26it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  92%|█████████▏| 12/13 [00:00<00:00, 86.40it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6:  92%|█████████▏| 12/13 [00:00<00:00, 86.28it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 86.51it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 86.38it/s, v_num=ld_3, val_loss=0.581, train_loss=0.533]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 78.41it/s, v_num=ld_3, val_loss=0.595, train_loss=0.533]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 78.13it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 6:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]         
    Epoch 7:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:   8%|▊         | 1/13 [00:00<00:00, 85.77it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:   8%|▊         | 1/13 [00:00<00:00, 84.29it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  15%|█▌        | 2/13 [00:00<00:00, 86.42it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  15%|█▌        | 2/13 [00:00<00:00, 85.60it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  23%|██▎       | 3/13 [00:00<00:00, 85.28it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  23%|██▎       | 3/13 [00:00<00:00, 84.70it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  31%|███       | 4/13 [00:00<00:00, 85.64it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  31%|███       | 4/13 [00:00<00:00, 85.26it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  38%|███▊      | 5/13 [00:00<00:00, 85.85it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  38%|███▊      | 5/13 [00:00<00:00, 85.50it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  46%|████▌     | 6/13 [00:00<00:00, 86.10it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  46%|████▌     | 6/13 [00:00<00:00, 85.85it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  54%|█████▍    | 7/13 [00:00<00:00, 85.91it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  54%|█████▍    | 7/13 [00:00<00:00, 85.69it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  62%|██████▏   | 8/13 [00:00<00:00, 85.76it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  62%|██████▏   | 8/13 [00:00<00:00, 85.56it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  69%|██████▉   | 9/13 [00:00<00:00, 85.38it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  69%|██████▉   | 9/13 [00:00<00:00, 85.21it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  77%|███████▋  | 10/13 [00:00<00:00, 85.40it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  77%|███████▋  | 10/13 [00:00<00:00, 85.24it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  85%|████████▍ | 11/13 [00:00<00:00, 85.32it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  85%|████████▍ | 11/13 [00:00<00:00, 85.19it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  92%|█████████▏| 12/13 [00:00<00:00, 85.12it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7:  92%|█████████▏| 12/13 [00:00<00:00, 85.00it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 85.29it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 85.18it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 77.37it/s, v_num=ld_3, val_loss=0.595, train_loss=0.522]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 77.08it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 7:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]         
    Epoch 8:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:   8%|▊         | 1/13 [00:00<00:00, 80.77it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:   8%|▊         | 1/13 [00:00<00:00, 79.30it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  15%|█▌        | 2/13 [00:00<00:00, 82.95it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  15%|█▌        | 2/13 [00:00<00:00, 82.24it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  23%|██▎       | 3/13 [00:00<00:00, 83.47it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  23%|██▎       | 3/13 [00:00<00:00, 82.94it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  31%|███       | 4/13 [00:00<00:00, 83.60it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  31%|███       | 4/13 [00:00<00:00, 83.19it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  38%|███▊      | 5/13 [00:00<00:00, 83.98it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  38%|███▊      | 5/13 [00:00<00:00, 83.69it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  46%|████▌     | 6/13 [00:00<00:00, 84.32it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  46%|████▌     | 6/13 [00:00<00:00, 83.97it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  54%|█████▍    | 7/13 [00:00<00:00, 83.68it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  54%|█████▍    | 7/13 [00:00<00:00, 83.45it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  62%|██████▏   | 8/13 [00:00<00:00, 83.69it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  62%|██████▏   | 8/13 [00:00<00:00, 83.51it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  69%|██████▉   | 9/13 [00:00<00:00, 83.80it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  69%|██████▉   | 9/13 [00:00<00:00, 83.64it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  77%|███████▋  | 10/13 [00:00<00:00, 83.49it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  77%|███████▋  | 10/13 [00:00<00:00, 83.34it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  85%|████████▍ | 11/13 [00:00<00:00, 83.47it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  85%|████████▍ | 11/13 [00:00<00:00, 83.33it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  92%|█████████▏| 12/13 [00:00<00:00, 83.18it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8:  92%|█████████▏| 12/13 [00:00<00:00, 83.05it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 83.12it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 82.99it/s, v_num=ld_3, val_loss=0.595, train_loss=0.514]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 75.57it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 75.30it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 8:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]         
    Epoch 9:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:   8%|▊         | 1/13 [00:00<00:00, 84.02it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:   8%|▊         | 1/13 [00:00<00:00, 82.60it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  15%|█▌        | 2/13 [00:00<00:00, 85.09it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  15%|█▌        | 2/13 [00:00<00:00, 84.36it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  23%|██▎       | 3/13 [00:00<00:00, 85.07it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  23%|██▎       | 3/13 [00:00<00:00, 84.58it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  31%|███       | 4/13 [00:00<00:00, 85.30it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  31%|███       | 4/13 [00:00<00:00, 84.93it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  38%|███▊      | 5/13 [00:00<00:00, 84.84it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  38%|███▊      | 5/13 [00:00<00:00, 84.52it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  46%|████▌     | 6/13 [00:00<00:00, 84.90it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  46%|████▌     | 6/13 [00:00<00:00, 84.62it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  54%|█████▍    | 7/13 [00:00<00:00, 84.90it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  54%|█████▍    | 7/13 [00:00<00:00, 84.69it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  62%|██████▏   | 8/13 [00:00<00:00, 84.97it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  62%|██████▏   | 8/13 [00:00<00:00, 84.79it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  69%|██████▉   | 9/13 [00:00<00:00, 84.97it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  69%|██████▉   | 9/13 [00:00<00:00, 84.81it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  77%|███████▋  | 10/13 [00:00<00:00, 85.19it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  77%|███████▋  | 10/13 [00:00<00:00, 85.04it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  85%|████████▍ | 11/13 [00:00<00:00, 84.70it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  85%|████████▍ | 11/13 [00:00<00:00, 84.55it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  92%|█████████▏| 12/13 [00:00<00:00, 84.62it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9:  92%|█████████▏| 12/13 [00:00<00:00, 84.50it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 84.90it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 84.79it/s, v_num=ld_3, val_loss=0.567, train_loss=0.514]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 77.02it/s, v_num=ld_3, val_loss=0.576, train_loss=0.514]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 76.75it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 9:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]         
    Epoch 10:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:   8%|▊         | 1/13 [00:00<00:00, 83.26it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:   8%|▊         | 1/13 [00:00<00:00, 81.79it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  15%|█▌        | 2/13 [00:00<00:00, 82.75it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  15%|█▌        | 2/13 [00:00<00:00, 82.06it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  23%|██▎       | 3/13 [00:00<00:00, 81.72it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  23%|██▎       | 3/13 [00:00<00:00, 81.17it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  31%|███       | 4/13 [00:00<00:00, 82.19it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  31%|███       | 4/13 [00:00<00:00, 81.70it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  38%|███▊      | 5/13 [00:00<00:00, 82.47it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  38%|███▊      | 5/13 [00:00<00:00, 82.15it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  46%|████▌     | 6/13 [00:00<00:00, 82.52it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  46%|████▌     | 6/13 [00:00<00:00, 82.26it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  54%|█████▍    | 7/13 [00:00<00:00, 82.75it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  54%|█████▍    | 7/13 [00:00<00:00, 82.52it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  62%|██████▏   | 8/13 [00:00<00:00, 82.76it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  62%|██████▏   | 8/13 [00:00<00:00, 82.57it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  69%|██████▉   | 9/13 [00:00<00:00, 82.41it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  69%|██████▉   | 9/13 [00:00<00:00, 82.23it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  77%|███████▋  | 10/13 [00:00<00:00, 82.58it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  77%|███████▋  | 10/13 [00:00<00:00, 82.44it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  85%|████████▍ | 11/13 [00:00<00:00, 82.38it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  85%|████████▍ | 11/13 [00:00<00:00, 82.23it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  92%|█████████▏| 12/13 [00:00<00:00, 82.42it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10:  92%|█████████▏| 12/13 [00:00<00:00, 82.29it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 82.95it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 82.83it/s, v_num=ld_3, val_loss=0.576, train_loss=0.513]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 75.19it/s, v_num=ld_3, val_loss=0.623, train_loss=0.513]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 74.93it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 10:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]         
    Epoch 11:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:   8%|▊         | 1/13 [00:00<00:00, 81.38it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:   8%|▊         | 1/13 [00:00<00:00, 79.91it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  15%|█▌        | 2/13 [00:00<00:00, 83.02it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  15%|█▌        | 2/13 [00:00<00:00, 82.32it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  23%|██▎       | 3/13 [00:00<00:00, 84.03it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  23%|██▎       | 3/13 [00:00<00:00, 83.55it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  31%|███       | 4/13 [00:00<00:00, 84.23it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  31%|███       | 4/13 [00:00<00:00, 83.83it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  38%|███▊      | 5/13 [00:00<00:00, 84.38it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  38%|███▊      | 5/13 [00:00<00:00, 84.09it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  46%|████▌     | 6/13 [00:00<00:00, 84.66it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  46%|████▌     | 6/13 [00:00<00:00, 84.42it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  54%|█████▍    | 7/13 [00:00<00:00, 84.45it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  54%|█████▍    | 7/13 [00:00<00:00, 84.24it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  62%|██████▏   | 8/13 [00:00<00:00, 84.70it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  62%|██████▏   | 8/13 [00:00<00:00, 84.50it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  69%|██████▉   | 9/13 [00:00<00:00, 84.78it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  69%|██████▉   | 9/13 [00:00<00:00, 84.62it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  77%|███████▋  | 10/13 [00:00<00:00, 84.92it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  77%|███████▋  | 10/13 [00:00<00:00, 84.77it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  85%|████████▍ | 11/13 [00:00<00:00, 84.96it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  85%|████████▍ | 11/13 [00:00<00:00, 84.80it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  92%|█████████▏| 12/13 [00:00<00:00, 85.00it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11:  92%|█████████▏| 12/13 [00:00<00:00, 84.88it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 85.11it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 84.99it/s, v_num=ld_3, val_loss=0.623, train_loss=0.525]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 77.30it/s, v_num=ld_3, val_loss=0.615, train_loss=0.525]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 77.02it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 11:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]         
    Epoch 12:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:   8%|▊         | 1/13 [00:00<00:00, 85.45it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:   8%|▊         | 1/13 [00:00<00:00, 83.99it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  15%|█▌        | 2/13 [00:00<00:00, 86.10it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  15%|█▌        | 2/13 [00:00<00:00, 85.28it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  23%|██▎       | 3/13 [00:00<00:00, 86.46it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  23%|██▎       | 3/13 [00:00<00:00, 85.95it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  31%|███       | 4/13 [00:00<00:00, 86.37it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  31%|███       | 4/13 [00:00<00:00, 85.99it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  38%|███▊      | 5/13 [00:00<00:00, 85.56it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  38%|███▊      | 5/13 [00:00<00:00, 85.21it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  46%|████▌     | 6/13 [00:00<00:00, 85.13it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  46%|████▌     | 6/13 [00:00<00:00, 84.89it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  54%|█████▍    | 7/13 [00:00<00:00, 85.33it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  54%|█████▍    | 7/13 [00:00<00:00, 85.12it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  62%|██████▏   | 8/13 [00:00<00:00, 85.38it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  62%|██████▏   | 8/13 [00:00<00:00, 85.19it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  69%|██████▉   | 9/13 [00:00<00:00, 85.57it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  69%|██████▉   | 9/13 [00:00<00:00, 85.39it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  77%|███████▋  | 10/13 [00:00<00:00, 85.71it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  77%|███████▋  | 10/13 [00:00<00:00, 85.56it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  85%|████████▍ | 11/13 [00:00<00:00, 85.41it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  85%|████████▍ | 11/13 [00:00<00:00, 85.27it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  92%|█████████▏| 12/13 [00:00<00:00, 85.37it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12:  92%|█████████▏| 12/13 [00:00<00:00, 85.25it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 85.67it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 85.55it/s, v_num=ld_3, val_loss=0.615, train_loss=0.529]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 77.80it/s, v_num=ld_3, val_loss=0.585, train_loss=0.529]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 77.52it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 12:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]         
    Epoch 13:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:   8%|▊         | 1/13 [00:00<00:00, 85.80it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:   8%|▊         | 1/13 [00:00<00:00, 84.22it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  15%|█▌        | 2/13 [00:00<00:00, 85.69it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  15%|█▌        | 2/13 [00:00<00:00, 84.96it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  23%|██▎       | 3/13 [00:00<00:00, 84.82it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  23%|██▎       | 3/13 [00:00<00:00, 84.30it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  31%|███       | 4/13 [00:00<00:00, 85.18it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  31%|███       | 4/13 [00:00<00:00, 84.81it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  38%|███▊      | 5/13 [00:00<00:00, 85.39it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  38%|███▊      | 5/13 [00:00<00:00, 85.10it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  46%|████▌     | 6/13 [00:00<00:00, 85.73it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  46%|████▌     | 6/13 [00:00<00:00, 85.48it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  54%|█████▍    | 7/13 [00:00<00:00, 85.88it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  54%|█████▍    | 7/13 [00:00<00:00, 85.66it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  62%|██████▏   | 8/13 [00:00<00:00, 85.85it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  62%|██████▏   | 8/13 [00:00<00:00, 85.66it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  69%|██████▉   | 9/13 [00:00<00:00, 85.52it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  69%|██████▉   | 9/13 [00:00<00:00, 85.34it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  77%|███████▋  | 10/13 [00:00<00:00, 85.64it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  77%|███████▋  | 10/13 [00:00<00:00, 85.47it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  85%|████████▍ | 11/13 [00:00<00:00, 85.84it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  85%|████████▍ | 11/13 [00:00<00:00, 85.71it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  92%|█████████▏| 12/13 [00:00<00:00, 85.91it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13:  92%|█████████▏| 12/13 [00:00<00:00, 85.78it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 86.30it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 86.18it/s, v_num=ld_3, val_loss=0.585, train_loss=0.525]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 78.11it/s, v_num=ld_3, val_loss=0.576, train_loss=0.525]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 77.82it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 13:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]         
    Epoch 14:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:   8%|▊         | 1/13 [00:00<00:00, 79.93it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:   8%|▊         | 1/13 [00:00<00:00, 78.52it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  15%|█▌        | 2/13 [00:00<00:00, 80.98it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  15%|█▌        | 2/13 [00:00<00:00, 80.32it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  23%|██▎       | 3/13 [00:00<00:00, 81.39it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  23%|██▎       | 3/13 [00:00<00:00, 80.93it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  31%|███       | 4/13 [00:00<00:00, 82.39it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  31%|███       | 4/13 [00:00<00:00, 82.04it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  38%|███▊      | 5/13 [00:00<00:00, 82.97it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  38%|███▊      | 5/13 [00:00<00:00, 82.66it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  46%|████▌     | 6/13 [00:00<00:00, 83.48it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  46%|████▌     | 6/13 [00:00<00:00, 83.25it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  54%|█████▍    | 7/13 [00:00<00:00, 83.35it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  54%|█████▍    | 7/13 [00:00<00:00, 83.13it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  62%|██████▏   | 8/13 [00:00<00:00, 83.60it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  62%|██████▏   | 8/13 [00:00<00:00, 83.42it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  69%|██████▉   | 9/13 [00:00<00:00, 83.89it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  69%|██████▉   | 9/13 [00:00<00:00, 83.73it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  77%|███████▋  | 10/13 [00:00<00:00, 83.78it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  77%|███████▋  | 10/13 [00:00<00:00, 83.64it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  85%|████████▍ | 11/13 [00:00<00:00, 83.93it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  85%|████████▍ | 11/13 [00:00<00:00, 83.78it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  92%|█████████▏| 12/13 [00:00<00:00, 84.11it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14:  92%|█████████▏| 12/13 [00:00<00:00, 83.99it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 84.19it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 84.07it/s, v_num=ld_3, val_loss=0.576, train_loss=0.510]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 76.55it/s, v_num=ld_3, val_loss=0.589, train_loss=0.510]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 76.29it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 14:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]         
    Epoch 15:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:   8%|▊         | 1/13 [00:00<00:00, 84.65it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:   8%|▊         | 1/13 [00:00<00:00, 83.22it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  15%|█▌        | 2/13 [00:00<00:00, 84.57it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  15%|█▌        | 2/13 [00:00<00:00, 83.85it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  23%|██▎       | 3/13 [00:00<00:00, 84.84it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  23%|██▎       | 3/13 [00:00<00:00, 84.35it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  31%|███       | 4/13 [00:00<00:00, 84.95it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  31%|███       | 4/13 [00:00<00:00, 84.55it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  38%|███▊      | 5/13 [00:00<00:00, 84.20it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  38%|███▊      | 5/13 [00:00<00:00, 83.88it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  46%|████▌     | 6/13 [00:00<00:00, 84.54it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  46%|████▌     | 6/13 [00:00<00:00, 84.29it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  54%|█████▍    | 7/13 [00:00<00:00, 84.84it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  54%|█████▍    | 7/13 [00:00<00:00, 84.63it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  62%|██████▏   | 8/13 [00:00<00:00, 84.74it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  62%|██████▏   | 8/13 [00:00<00:00, 84.56it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  69%|██████▉   | 9/13 [00:00<00:00, 84.80it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  69%|██████▉   | 9/13 [00:00<00:00, 84.62it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  77%|███████▋  | 10/13 [00:00<00:00, 84.79it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  77%|███████▋  | 10/13 [00:00<00:00, 84.64it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  85%|████████▍ | 11/13 [00:00<00:00, 84.37it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  85%|████████▍ | 11/13 [00:00<00:00, 84.22it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  92%|█████████▏| 12/13 [00:00<00:00, 84.51it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15:  92%|█████████▏| 12/13 [00:00<00:00, 84.39it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 84.93it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 84.80it/s, v_num=ld_3, val_loss=0.589, train_loss=0.519]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 77.22it/s, v_num=ld_3, val_loss=0.563, train_loss=0.519]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 76.96it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 15:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]         
    Epoch 16:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:   8%|▊         | 1/13 [00:00<00:00, 85.25it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:   8%|▊         | 1/13 [00:00<00:00, 83.80it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  15%|█▌        | 2/13 [00:00<00:00, 85.78it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  15%|█▌        | 2/13 [00:00<00:00, 85.03it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  23%|██▎       | 3/13 [00:00<00:00, 84.75it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  23%|██▎       | 3/13 [00:00<00:00, 84.18it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  31%|███       | 4/13 [00:00<00:00, 84.95it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  31%|███       | 4/13 [00:00<00:00, 84.59it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  38%|███▊      | 5/13 [00:00<00:00, 85.14it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  38%|███▊      | 5/13 [00:00<00:00, 84.84it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  46%|████▌     | 6/13 [00:00<00:00, 85.23it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  46%|████▌     | 6/13 [00:00<00:00, 84.98it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  54%|█████▍    | 7/13 [00:00<00:00, 85.09it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  54%|█████▍    | 7/13 [00:00<00:00, 84.88it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  62%|██████▏   | 8/13 [00:00<00:00, 85.26it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  62%|██████▏   | 8/13 [00:00<00:00, 85.08it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  69%|██████▉   | 9/13 [00:00<00:00, 84.91it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  69%|██████▉   | 9/13 [00:00<00:00, 84.73it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  77%|███████▋  | 10/13 [00:00<00:00, 84.94it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  77%|███████▋  | 10/13 [00:00<00:00, 84.79it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  85%|████████▍ | 11/13 [00:00<00:00, 85.00it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  85%|████████▍ | 11/13 [00:00<00:00, 84.87it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  92%|█████████▏| 12/13 [00:00<00:00, 85.07it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16:  92%|█████████▏| 12/13 [00:00<00:00, 84.94it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 85.49it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 85.37it/s, v_num=ld_3, val_loss=0.563, train_loss=0.507]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 77.68it/s, v_num=ld_3, val_loss=0.569, train_loss=0.507]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 77.39it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 16:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]         
    Epoch 17:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:   8%|▊         | 1/13 [00:00<00:00, 82.83it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:   8%|▊         | 1/13 [00:00<00:00, 81.04it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  15%|█▌        | 2/13 [00:00<00:00, 83.91it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  15%|█▌        | 2/13 [00:00<00:00, 83.20it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  23%|██▎       | 3/13 [00:00<00:00, 84.60it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  23%|██▎       | 3/13 [00:00<00:00, 84.11it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  31%|███       | 4/13 [00:00<00:00, 84.72it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  31%|███       | 4/13 [00:00<00:00, 84.36it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  38%|███▊      | 5/13 [00:00<00:00, 85.04it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  38%|███▊      | 5/13 [00:00<00:00, 84.72it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  46%|████▌     | 6/13 [00:00<00:00, 85.15it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  46%|████▌     | 6/13 [00:00<00:00, 84.90it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  54%|█████▍    | 7/13 [00:00<00:00, 84.72it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  54%|█████▍    | 7/13 [00:00<00:00, 84.50it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  62%|██████▏   | 8/13 [00:00<00:00, 84.74it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  62%|██████▏   | 8/13 [00:00<00:00, 84.55it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  69%|██████▉   | 9/13 [00:00<00:00, 84.77it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  69%|██████▉   | 9/13 [00:00<00:00, 84.60it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  77%|███████▋  | 10/13 [00:00<00:00, 84.80it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  77%|███████▋  | 10/13 [00:00<00:00, 84.64it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  85%|████████▍ | 11/13 [00:00<00:00, 84.84it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  85%|████████▍ | 11/13 [00:00<00:00, 84.71it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  92%|█████████▏| 12/13 [00:00<00:00, 84.76it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17:  92%|█████████▏| 12/13 [00:00<00:00, 84.64it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 84.87it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 84.74it/s, v_num=ld_3, val_loss=0.569, train_loss=0.503]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 77.12it/s, v_num=ld_3, val_loss=0.591, train_loss=0.503]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 76.85it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 17:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]         
    Epoch 18:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:   8%|▊         | 1/13 [00:00<00:00, 85.00it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:   8%|▊         | 1/13 [00:00<00:00, 83.56it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  15%|█▌        | 2/13 [00:00<00:00, 85.21it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  15%|█▌        | 2/13 [00:00<00:00, 84.48it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  23%|██▎       | 3/13 [00:00<00:00, 85.45it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  23%|██▎       | 3/13 [00:00<00:00, 84.96it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  31%|███       | 4/13 [00:00<00:00, 85.93it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  31%|███       | 4/13 [00:00<00:00, 85.56it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  38%|███▊      | 5/13 [00:00<00:00, 85.18it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  38%|███▊      | 5/13 [00:00<00:00, 84.86it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  46%|████▌     | 6/13 [00:00<00:00, 85.38it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  46%|████▌     | 6/13 [00:00<00:00, 85.11it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  54%|█████▍    | 7/13 [00:00<00:00, 85.52it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  54%|█████▍    | 7/13 [00:00<00:00, 85.31it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  62%|██████▏   | 8/13 [00:00<00:00, 85.39it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  62%|██████▏   | 8/13 [00:00<00:00, 85.20it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  69%|██████▉   | 9/13 [00:00<00:00, 85.36it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  69%|██████▉   | 9/13 [00:00<00:00, 85.19it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  77%|███████▋  | 10/13 [00:00<00:00, 85.29it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  77%|███████▋  | 10/13 [00:00<00:00, 85.12it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  85%|████████▍ | 11/13 [00:00<00:00, 84.98it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  85%|████████▍ | 11/13 [00:00<00:00, 84.83it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  92%|█████████▏| 12/13 [00:00<00:00, 84.97it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18:  92%|█████████▏| 12/13 [00:00<00:00, 84.83it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 85.43it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 85.30it/s, v_num=ld_3, val_loss=0.591, train_loss=0.509]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 77.62it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 77.35it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 18:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]         
    Epoch 19:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:   8%|▊         | 1/13 [00:00<00:00, 85.63it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:   8%|▊         | 1/13 [00:00<00:00, 84.03it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  15%|█▌        | 2/13 [00:00<00:00, 85.80it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  15%|█▌        | 2/13 [00:00<00:00, 85.07it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  23%|██▎       | 3/13 [00:00<00:00, 84.92it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  23%|██▎       | 3/13 [00:00<00:00, 84.37it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  31%|███       | 4/13 [00:00<00:00, 84.26it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  31%|███       | 4/13 [00:00<00:00, 83.90it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  38%|███▊      | 5/13 [00:00<00:00, 84.60it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  38%|███▊      | 5/13 [00:00<00:00, 84.31it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  46%|████▌     | 6/13 [00:00<00:00, 84.75it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  46%|████▌     | 6/13 [00:00<00:00, 84.51it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  54%|█████▍    | 7/13 [00:00<00:00, 84.95it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  54%|█████▍    | 7/13 [00:00<00:00, 84.74it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  62%|██████▏   | 8/13 [00:00<00:00, 84.78it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  62%|██████▏   | 8/13 [00:00<00:00, 84.59it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  69%|██████▉   | 9/13 [00:00<00:00, 83.89it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  69%|██████▉   | 9/13 [00:00<00:00, 83.71it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  77%|███████▋  | 10/13 [00:00<00:00, 83.98it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  77%|███████▋  | 10/13 [00:00<00:00, 83.84it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  85%|████████▍ | 11/13 [00:00<00:00, 83.99it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  85%|████████▍ | 11/13 [00:00<00:00, 83.85it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  92%|█████████▏| 12/13 [00:00<00:00, 83.90it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19:  92%|█████████▏| 12/13 [00:00<00:00, 83.78it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 84.32it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 84.21it/s, v_num=ld_3, val_loss=0.595, train_loss=0.509]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 76.48it/s, v_num=ld_3, val_loss=0.574, train_loss=0.509]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 76.22it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 19:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]         
    Epoch 20:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:   8%|▊         | 1/13 [00:00<00:00, 79.79it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:   8%|▊         | 1/13 [00:00<00:00, 78.41it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  15%|█▌        | 2/13 [00:00<00:00, 82.35it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  15%|█▌        | 2/13 [00:00<00:00, 81.66it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  23%|██▎       | 3/13 [00:00<00:00, 82.72it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  23%|██▎       | 3/13 [00:00<00:00, 82.25it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  31%|███       | 4/13 [00:00<00:00, 83.32it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  31%|███       | 4/13 [00:00<00:00, 82.96it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  38%|███▊      | 5/13 [00:00<00:00, 83.32it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  38%|███▊      | 5/13 [00:00<00:00, 83.04it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  46%|████▌     | 6/13 [00:00<00:00, 83.51it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  46%|████▌     | 6/13 [00:00<00:00, 83.27it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  54%|█████▍    | 7/13 [00:00<00:00, 82.70it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  54%|█████▍    | 7/13 [00:00<00:00, 82.47it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  62%|██████▏   | 8/13 [00:00<00:00, 82.85it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  62%|██████▏   | 8/13 [00:00<00:00, 82.67it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  69%|██████▉   | 9/13 [00:00<00:00, 82.89it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  69%|██████▉   | 9/13 [00:00<00:00, 82.74it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  77%|███████▋  | 10/13 [00:00<00:00, 83.09it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  77%|███████▋  | 10/13 [00:00<00:00, 82.93it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  85%|████████▍ | 11/13 [00:00<00:00, 83.22it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  85%|████████▍ | 11/13 [00:00<00:00, 83.09it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  92%|█████████▏| 12/13 [00:00<00:00, 83.37it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20:  92%|█████████▏| 12/13 [00:00<00:00, 83.25it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 83.48it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 83.36it/s, v_num=ld_3, val_loss=0.574, train_loss=0.502]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 75.82it/s, v_num=ld_3, val_loss=0.571, train_loss=0.502]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 75.55it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 20:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]         
    Epoch 21:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:   8%|▊         | 1/13 [00:00<00:00, 82.11it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:   8%|▊         | 1/13 [00:00<00:00, 80.74it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  15%|█▌        | 2/13 [00:00<00:00, 82.89it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  15%|█▌        | 2/13 [00:00<00:00, 82.18it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  23%|██▎       | 3/13 [00:00<00:00, 82.87it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  23%|██▎       | 3/13 [00:00<00:00, 82.40it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  31%|███       | 4/13 [00:00<00:00, 82.92it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  31%|███       | 4/13 [00:00<00:00, 82.57it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  38%|███▊      | 5/13 [00:00<00:00, 82.49it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  38%|███▊      | 5/13 [00:00<00:00, 82.16it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  46%|████▌     | 6/13 [00:00<00:00, 82.48it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  46%|████▌     | 6/13 [00:00<00:00, 82.22it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  54%|█████▍    | 7/13 [00:00<00:00, 82.62it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  54%|█████▍    | 7/13 [00:00<00:00, 82.39it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  62%|██████▏   | 8/13 [00:00<00:00, 82.36it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  62%|██████▏   | 8/13 [00:00<00:00, 82.17it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  69%|██████▉   | 9/13 [00:00<00:00, 82.35it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  69%|██████▉   | 9/13 [00:00<00:00, 82.19it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  77%|███████▋  | 10/13 [00:00<00:00, 82.38it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  77%|███████▋  | 10/13 [00:00<00:00, 82.23it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  85%|████████▍ | 11/13 [00:00<00:00, 81.91it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  85%|████████▍ | 11/13 [00:00<00:00, 81.77it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  92%|█████████▏| 12/13 [00:00<00:00, 81.89it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21:  92%|█████████▏| 12/13 [00:00<00:00, 81.78it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 82.22it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 82.11it/s, v_num=ld_3, val_loss=0.571, train_loss=0.499]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 74.60it/s, v_num=ld_3, val_loss=0.599, train_loss=0.499]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 74.33it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 21:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]         
    Epoch 22:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:   8%|▊         | 1/13 [00:00<00:00, 82.76it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:   8%|▊         | 1/13 [00:00<00:00, 81.25it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  15%|█▌        | 2/13 [00:00<00:00, 82.05it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  15%|█▌        | 2/13 [00:00<00:00, 81.33it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  23%|██▎       | 3/13 [00:00<00:00, 80.08it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  23%|██▎       | 3/13 [00:00<00:00, 79.61it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  31%|███       | 4/13 [00:00<00:00, 80.44it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  31%|███       | 4/13 [00:00<00:00, 80.10it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  38%|███▊      | 5/13 [00:00<00:00, 81.24it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  38%|███▊      | 5/13 [00:00<00:00, 80.82it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  46%|████▌     | 6/13 [00:00<00:00, 81.58it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  46%|████▌     | 6/13 [00:00<00:00, 81.36it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  54%|█████▍    | 7/13 [00:00<00:00, 81.77it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  54%|█████▍    | 7/13 [00:00<00:00, 81.58it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  62%|██████▏   | 8/13 [00:00<00:00, 81.88it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  62%|██████▏   | 8/13 [00:00<00:00, 81.71it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  69%|██████▉   | 9/13 [00:00<00:00, 81.79it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  69%|██████▉   | 9/13 [00:00<00:00, 81.61it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  77%|███████▋  | 10/13 [00:00<00:00, 81.82it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  77%|███████▋  | 10/13 [00:00<00:00, 81.68it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  85%|████████▍ | 11/13 [00:00<00:00, 81.91it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  85%|████████▍ | 11/13 [00:00<00:00, 81.78it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  92%|█████████▏| 12/13 [00:00<00:00, 81.96it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22:  92%|█████████▏| 12/13 [00:00<00:00, 81.84it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 82.52it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 82.41it/s, v_num=ld_3, val_loss=0.599, train_loss=0.504]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 74.79it/s, v_num=ld_3, val_loss=0.613, train_loss=0.504]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 74.53it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 22:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]         
    Epoch 23:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:   8%|▊         | 1/13 [00:00<00:00, 78.29it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:   8%|▊         | 1/13 [00:00<00:00, 76.98it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  15%|█▌        | 2/13 [00:00<00:00, 81.14it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  15%|█▌        | 2/13 [00:00<00:00, 80.46it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  23%|██▎       | 3/13 [00:00<00:00, 82.39it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  23%|██▎       | 3/13 [00:00<00:00, 81.92it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  31%|███       | 4/13 [00:00<00:00, 83.09it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  31%|███       | 4/13 [00:00<00:00, 82.74it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  38%|███▊      | 5/13 [00:00<00:00, 83.58it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  38%|███▊      | 5/13 [00:00<00:00, 83.29it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  46%|████▌     | 6/13 [00:00<00:00, 83.75it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  46%|████▌     | 6/13 [00:00<00:00, 83.51it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  54%|█████▍    | 7/13 [00:00<00:00, 82.79it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  54%|█████▍    | 7/13 [00:00<00:00, 82.58it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  62%|██████▏   | 8/13 [00:00<00:00, 83.05it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  62%|██████▏   | 8/13 [00:00<00:00, 82.87it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  69%|██████▉   | 9/13 [00:00<00:00, 83.30it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  69%|██████▉   | 9/13 [00:00<00:00, 83.13it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  77%|███████▋  | 10/13 [00:00<00:00, 83.51it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  77%|███████▋  | 10/13 [00:00<00:00, 83.37it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  85%|████████▍ | 11/13 [00:00<00:00, 83.72it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  85%|████████▍ | 11/13 [00:00<00:00, 83.59it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  92%|█████████▏| 12/13 [00:00<00:00, 83.91it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23:  92%|█████████▏| 12/13 [00:00<00:00, 83.77it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 84.08it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 83.97it/s, v_num=ld_3, val_loss=0.613, train_loss=0.510]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 76.43it/s, v_num=ld_3, val_loss=0.585, train_loss=0.510]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 76.16it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 23:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]         
    Epoch 24:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:   8%|▊         | 1/13 [00:00<00:00, 82.65it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:   8%|▊         | 1/13 [00:00<00:00, 81.27it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  15%|█▌        | 2/13 [00:00<00:00, 82.47it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  15%|█▌        | 2/13 [00:00<00:00, 81.78it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  23%|██▎       | 3/13 [00:00<00:00, 83.43it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  23%|██▎       | 3/13 [00:00<00:00, 82.96it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  31%|███       | 4/13 [00:00<00:00, 83.91it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  31%|███       | 4/13 [00:00<00:00, 83.51it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  38%|███▊      | 5/13 [00:00<00:00, 83.48it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  38%|███▊      | 5/13 [00:00<00:00, 83.20it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  46%|████▌     | 6/13 [00:00<00:00, 83.91it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  46%|████▌     | 6/13 [00:00<00:00, 83.67it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  54%|█████▍    | 7/13 [00:00<00:00, 82.84it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  54%|█████▍    | 7/13 [00:00<00:00, 82.64it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  62%|██████▏   | 8/13 [00:00<00:00, 83.01it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  62%|██████▏   | 8/13 [00:00<00:00, 82.83it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  69%|██████▉   | 9/13 [00:00<00:00, 83.15it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  69%|██████▉   | 9/13 [00:00<00:00, 82.99it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  77%|███████▋  | 10/13 [00:00<00:00, 83.22it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  77%|███████▋  | 10/13 [00:00<00:00, 83.07it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  85%|████████▍ | 11/13 [00:00<00:00, 82.82it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  85%|████████▍ | 11/13 [00:00<00:00, 82.67it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  92%|█████████▏| 12/13 [00:00<00:00, 82.90it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24:  92%|█████████▏| 12/13 [00:00<00:00, 82.78it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 83.37it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 83.26it/s, v_num=ld_3, val_loss=0.585, train_loss=0.505]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 75.80it/s, v_num=ld_3, val_loss=0.582, train_loss=0.505]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 75.53it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 24:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]         
    Epoch 25:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:   8%|▊         | 1/13 [00:00<00:00, 82.06it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:   8%|▊         | 1/13 [00:00<00:00, 80.71it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  15%|█▌        | 2/13 [00:00<00:00, 84.16it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  15%|█▌        | 2/13 [00:00<00:00, 83.38it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  23%|██▎       | 3/13 [00:00<00:00, 83.37it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  23%|██▎       | 3/13 [00:00<00:00, 82.84it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  31%|███       | 4/13 [00:00<00:00, 83.64it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  31%|███       | 4/13 [00:00<00:00, 83.24it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  38%|███▊      | 5/13 [00:00<00:00, 84.13it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  38%|███▊      | 5/13 [00:00<00:00, 83.83it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  46%|████▌     | 6/13 [00:00<00:00, 84.18it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  46%|████▌     | 6/13 [00:00<00:00, 83.93it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  54%|█████▍    | 7/13 [00:00<00:00, 84.35it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  54%|█████▍    | 7/13 [00:00<00:00, 84.14it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  62%|██████▏   | 8/13 [00:00<00:00, 84.26it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  62%|██████▏   | 8/13 [00:00<00:00, 84.04it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  69%|██████▉   | 9/13 [00:00<00:00, 83.45it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  69%|██████▉   | 9/13 [00:00<00:00, 83.24it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  77%|███████▋  | 10/13 [00:00<00:00, 83.12it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  77%|███████▋  | 10/13 [00:00<00:00, 82.96it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  85%|████████▍ | 11/13 [00:00<00:00, 82.85it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  85%|████████▍ | 11/13 [00:00<00:00, 82.69it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  92%|█████████▏| 12/13 [00:00<00:00, 82.65it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25:  92%|█████████▏| 12/13 [00:00<00:00, 82.52it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 82.85it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 82.72it/s, v_num=ld_3, val_loss=0.582, train_loss=0.517]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 75.29it/s, v_num=ld_3, val_loss=0.611, train_loss=0.517]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 75.02it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 25:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]         
    Epoch 26:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:   8%|▊         | 1/13 [00:00<00:00, 80.34it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:   8%|▊         | 1/13 [00:00<00:00, 78.94it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  15%|█▌        | 2/13 [00:00<00:00, 81.85it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  15%|█▌        | 2/13 [00:00<00:00, 81.18it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  23%|██▎       | 3/13 [00:00<00:00, 82.54it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  23%|██▎       | 3/13 [00:00<00:00, 82.08it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  31%|███       | 4/13 [00:00<00:00, 81.46it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  31%|███       | 4/13 [00:00<00:00, 81.12it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  38%|███▊      | 5/13 [00:00<00:00, 81.31it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  38%|███▊      | 5/13 [00:00<00:00, 81.03it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  46%|████▌     | 6/13 [00:00<00:00, 81.31it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  46%|████▌     | 6/13 [00:00<00:00, 81.08it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  54%|█████▍    | 7/13 [00:00<00:00, 81.14it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  54%|█████▍    | 7/13 [00:00<00:00, 80.93it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  62%|██████▏   | 8/13 [00:00<00:00, 80.04it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  62%|██████▏   | 8/13 [00:00<00:00, 79.86it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  69%|██████▉   | 9/13 [00:00<00:00, 80.53it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  69%|██████▉   | 9/13 [00:00<00:00, 80.37it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  77%|███████▋  | 10/13 [00:00<00:00, 80.00it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  77%|███████▋  | 10/13 [00:00<00:00, 79.85it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  85%|████████▍ | 11/13 [00:00<00:00, 80.47it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  85%|████████▍ | 11/13 [00:00<00:00, 80.35it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  92%|█████████▏| 12/13 [00:00<00:00, 80.89it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26:  92%|█████████▏| 12/13 [00:00<00:00, 80.78it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26: 100%|██████████| 13/13 [00:00<00:00, 81.35it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26: 100%|██████████| 13/13 [00:00<00:00, 81.22it/s, v_num=ld_3, val_loss=0.611, train_loss=0.509]
    Epoch 26: 100%|██████████| 13/13 [00:00<00:00, 74.18it/s, v_num=ld_3, val_loss=0.578, train_loss=0.509]
    Epoch 26: 100%|██████████| 13/13 [00:00<00:00, 73.93it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 26:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]         
    Epoch 27:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:   8%|▊         | 1/13 [00:00<00:00, 83.31it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:   8%|▊         | 1/13 [00:00<00:00, 81.83it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  15%|█▌        | 2/13 [00:00<00:00, 84.10it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  15%|█▌        | 2/13 [00:00<00:00, 83.39it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  23%|██▎       | 3/13 [00:00<00:00, 84.23it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  23%|██▎       | 3/13 [00:00<00:00, 83.75it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  31%|███       | 4/13 [00:00<00:00, 83.43it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  31%|███       | 4/13 [00:00<00:00, 83.08it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  38%|███▊      | 5/13 [00:00<00:00, 83.26it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  38%|███▊      | 5/13 [00:00<00:00, 82.95it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  46%|████▌     | 6/13 [00:00<00:00, 83.48it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  46%|████▌     | 6/13 [00:00<00:00, 83.24it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  54%|█████▍    | 7/13 [00:00<00:00, 83.56it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  54%|█████▍    | 7/13 [00:00<00:00, 83.36it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  62%|██████▏   | 8/13 [00:00<00:00, 83.77it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  62%|██████▏   | 8/13 [00:00<00:00, 83.57it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  69%|██████▉   | 9/13 [00:00<00:00, 83.07it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  69%|██████▉   | 9/13 [00:00<00:00, 82.91it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  77%|███████▋  | 10/13 [00:00<00:00, 82.35it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  77%|███████▋  | 10/13 [00:00<00:00, 82.20it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  85%|████████▍ | 11/13 [00:00<00:00, 82.40it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  85%|████████▍ | 11/13 [00:00<00:00, 82.25it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  92%|█████████▏| 12/13 [00:00<00:00, 82.52it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27:  92%|█████████▏| 12/13 [00:00<00:00, 82.39it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27: 100%|██████████| 13/13 [00:00<00:00, 83.15it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27: 100%|██████████| 13/13 [00:00<00:00, 83.03it/s, v_num=ld_3, val_loss=0.578, train_loss=0.523]
    Epoch 27: 100%|██████████| 13/13 [00:00<00:00, 75.79it/s, v_num=ld_3, val_loss=0.588, train_loss=0.523]
    Epoch 27: 100%|██████████| 13/13 [00:00<00:00, 75.52it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 27:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]         
    Epoch 28:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:   8%|▊         | 1/13 [00:00<00:00, 86.46it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:   8%|▊         | 1/13 [00:00<00:00, 84.97it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  15%|█▌        | 2/13 [00:00<00:00, 81.08it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  15%|█▌        | 2/13 [00:00<00:00, 80.35it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  23%|██▎       | 3/13 [00:00<00:00, 81.83it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  23%|██▎       | 3/13 [00:00<00:00, 81.28it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  31%|███       | 4/13 [00:00<00:00, 79.75it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  31%|███       | 4/13 [00:00<00:00, 79.43it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  38%|███▊      | 5/13 [00:00<00:00, 80.23it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  38%|███▊      | 5/13 [00:00<00:00, 79.97it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  46%|████▌     | 6/13 [00:00<00:00, 80.31it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  46%|████▌     | 6/13 [00:00<00:00, 80.04it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  54%|█████▍    | 7/13 [00:00<00:00, 80.01it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  54%|█████▍    | 7/13 [00:00<00:00, 79.82it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  62%|██████▏   | 8/13 [00:00<00:00, 80.61it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  62%|██████▏   | 8/13 [00:00<00:00, 80.44it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  69%|██████▉   | 9/13 [00:00<00:00, 80.77it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  69%|██████▉   | 9/13 [00:00<00:00, 80.60it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  77%|███████▋  | 10/13 [00:00<00:00, 80.83it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  77%|███████▋  | 10/13 [00:00<00:00, 80.68it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  85%|████████▍ | 11/13 [00:00<00:00, 80.83it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  85%|████████▍ | 11/13 [00:00<00:00, 80.71it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  92%|█████████▏| 12/13 [00:00<00:00, 81.09it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28:  92%|█████████▏| 12/13 [00:00<00:00, 80.98it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28: 100%|██████████| 13/13 [00:00<00:00, 81.69it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28: 100%|██████████| 13/13 [00:00<00:00, 81.58it/s, v_num=ld_3, val_loss=0.588, train_loss=0.511]
    Epoch 28: 100%|██████████| 13/13 [00:00<00:00, 74.52it/s, v_num=ld_3, val_loss=0.568, train_loss=0.511]
    Epoch 28: 100%|██████████| 13/13 [00:00<00:00, 74.26it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 28:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]         
    Epoch 29:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:   8%|▊         | 1/13 [00:00<00:00, 81.54it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:   8%|▊         | 1/13 [00:00<00:00, 80.06it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  15%|█▌        | 2/13 [00:00<00:00, 83.69it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  15%|█▌        | 2/13 [00:00<00:00, 82.98it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  23%|██▎       | 3/13 [00:00<00:00, 84.19it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  23%|██▎       | 3/13 [00:00<00:00, 83.71it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  31%|███       | 4/13 [00:00<00:00, 84.00it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  31%|███       | 4/13 [00:00<00:00, 83.65it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  38%|███▊      | 5/13 [00:00<00:00, 83.32it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  38%|███▊      | 5/13 [00:00<00:00, 83.00it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  46%|████▌     | 6/13 [00:00<00:00, 83.77it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  46%|████▌     | 6/13 [00:00<00:00, 83.53it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  54%|█████▍    | 7/13 [00:00<00:00, 83.41it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  54%|█████▍    | 7/13 [00:00<00:00, 83.17it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  62%|██████▏   | 8/13 [00:00<00:00, 82.56it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  62%|██████▏   | 8/13 [00:00<00:00, 82.39it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  69%|██████▉   | 9/13 [00:00<00:00, 82.88it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  69%|██████▉   | 9/13 [00:00<00:00, 82.72it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  77%|███████▋  | 10/13 [00:00<00:00, 83.03it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  77%|███████▋  | 10/13 [00:00<00:00, 82.89it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  85%|████████▍ | 11/13 [00:00<00:00, 83.15it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  85%|████████▍ | 11/13 [00:00<00:00, 83.02it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  92%|█████████▏| 12/13 [00:00<00:00, 83.43it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29:  92%|█████████▏| 12/13 [00:00<00:00, 83.31it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29: 100%|██████████| 13/13 [00:00<00:00, 83.46it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29: 100%|██████████| 13/13 [00:00<00:00, 83.35it/s, v_num=ld_3, val_loss=0.568, train_loss=0.508]
    Epoch 29: 100%|██████████| 13/13 [00:00<00:00, 76.02it/s, v_num=ld_3, val_loss=0.569, train_loss=0.508]
    Epoch 29: 100%|██████████| 13/13 [00:00<00:00, 75.75it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 29:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]         
    Epoch 30:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:   8%|▊         | 1/13 [00:00<00:00, 84.36it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:   8%|▊         | 1/13 [00:00<00:00, 82.78it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  15%|█▌        | 2/13 [00:00<00:00, 83.97it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  15%|█▌        | 2/13 [00:00<00:00, 83.19it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  23%|██▎       | 3/13 [00:00<00:00, 82.28it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  23%|██▎       | 3/13 [00:00<00:00, 81.82it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  31%|███       | 4/13 [00:00<00:00, 82.68it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  31%|███       | 4/13 [00:00<00:00, 82.33it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  38%|███▊      | 5/13 [00:00<00:00, 81.95it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  38%|███▊      | 5/13 [00:00<00:00, 81.67it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  46%|████▌     | 6/13 [00:00<00:00, 81.50it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  46%|████▌     | 6/13 [00:00<00:00, 81.27it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  54%|█████▍    | 7/13 [00:00<00:00, 81.96it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  54%|█████▍    | 7/13 [00:00<00:00, 81.76it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  62%|██████▏   | 8/13 [00:00<00:00, 81.90it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  62%|██████▏   | 8/13 [00:00<00:00, 81.72it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  69%|██████▉   | 9/13 [00:00<00:00, 81.10it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  69%|██████▉   | 9/13 [00:00<00:00, 80.94it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  77%|███████▋  | 10/13 [00:00<00:00, 81.19it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  77%|███████▋  | 10/13 [00:00<00:00, 81.06it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  85%|████████▍ | 11/13 [00:00<00:00, 81.03it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  85%|████████▍ | 11/13 [00:00<00:00, 80.89it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  92%|█████████▏| 12/13 [00:00<00:00, 80.80it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30:  92%|█████████▏| 12/13 [00:00<00:00, 80.69it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30: 100%|██████████| 13/13 [00:00<00:00, 81.49it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30: 100%|██████████| 13/13 [00:00<00:00, 81.39it/s, v_num=ld_3, val_loss=0.569, train_loss=0.504]
    Epoch 30: 100%|██████████| 13/13 [00:00<00:00, 74.32it/s, v_num=ld_3, val_loss=0.581, train_loss=0.504]
    Epoch 30: 100%|██████████| 13/13 [00:00<00:00, 74.06it/s, v_num=ld_3, val_loss=0.581, train_loss=0.503]
    Epoch 30: 100%|██████████| 13/13 [00:00<00:00, 73.78it/s, v_num=ld_3, val_loss=0.581, train_loss=0.503]
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
         Validate metric           DataLoader 0
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
            AUROC_val           0.9337616562843323
          Accuracy_val          0.8799999952316284
            val_loss            0.5809109807014465
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────

    Training: |          | 0/? [00:00<?, ?it/s]
    Training:   0%|          | 0/13 [00:00<?, ?it/s]
    Epoch 0:   0%|          | 0/13 [00:00<?, ?it/s] 
    Epoch 0:   8%|▊         | 1/13 [00:00<00:00, 50.79it/s]
    Epoch 0:   8%|▊         | 1/13 [00:00<00:00, 49.95it/s, v_num=ld_4]
    Epoch 0:  15%|█▌        | 2/13 [00:00<00:00, 53.98it/s, v_num=ld_4]
    Epoch 0:  15%|█▌        | 2/13 [00:00<00:00, 53.55it/s, v_num=ld_4]
    Epoch 0:  23%|██▎       | 3/13 [00:00<00:00, 55.48it/s, v_num=ld_4]
    Epoch 0:  23%|██▎       | 3/13 [00:00<00:00, 55.19it/s, v_num=ld_4]
    Epoch 0:  31%|███       | 4/13 [00:00<00:00, 56.70it/s, v_num=ld_4]
    Epoch 0:  31%|███       | 4/13 [00:00<00:00, 56.51it/s, v_num=ld_4]
    Epoch 0:  38%|███▊      | 5/13 [00:00<00:00, 60.87it/s, v_num=ld_4]
    Epoch 0:  38%|███▊      | 5/13 [00:00<00:00, 60.73it/s, v_num=ld_4]
    Epoch 0:  46%|████▌     | 6/13 [00:00<00:00, 64.02it/s, v_num=ld_4]
    Epoch 0:  46%|████▌     | 6/13 [00:00<00:00, 63.87it/s, v_num=ld_4]
    Epoch 0:  54%|█████▍    | 7/13 [00:00<00:00, 66.21it/s, v_num=ld_4]
    Epoch 0:  54%|█████▍    | 7/13 [00:00<00:00, 66.07it/s, v_num=ld_4]
    Epoch 0:  62%|██████▏   | 8/13 [00:00<00:00, 68.23it/s, v_num=ld_4]
    Epoch 0:  62%|██████▏   | 8/13 [00:00<00:00, 68.12it/s, v_num=ld_4]
    Epoch 0:  69%|██████▉   | 9/13 [00:00<00:00, 70.05it/s, v_num=ld_4]
    Epoch 0:  69%|██████▉   | 9/13 [00:00<00:00, 69.95it/s, v_num=ld_4]
    Epoch 0:  77%|███████▋  | 10/13 [00:00<00:00, 71.47it/s, v_num=ld_4]
    Epoch 0:  77%|███████▋  | 10/13 [00:00<00:00, 71.37it/s, v_num=ld_4]
    Epoch 0:  85%|████████▍ | 11/13 [00:00<00:00, 72.71it/s, v_num=ld_4]
    Epoch 0:  85%|████████▍ | 11/13 [00:00<00:00, 72.62it/s, v_num=ld_4]
    Epoch 0:  92%|█████████▏| 12/13 [00:00<00:00, 73.81it/s, v_num=ld_4]
    Epoch 0:  92%|█████████▏| 12/13 [00:00<00:00, 73.70it/s, v_num=ld_4]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 74.66it/s, v_num=ld_4]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 74.58it/s, v_num=ld_4]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 68.38it/s, v_num=ld_4, val_loss=0.661]
    Epoch 0: 100%|██████████| 13/13 [00:00<00:00, 68.17it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 0:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]         
    Epoch 1:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:   8%|▊         | 1/13 [00:00<00:00, 87.79it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:   8%|▊         | 1/13 [00:00<00:00, 86.25it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  15%|█▌        | 2/13 [00:00<00:00, 87.91it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  15%|█▌        | 2/13 [00:00<00:00, 87.14it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  23%|██▎       | 3/13 [00:00<00:00, 85.49it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  23%|██▎       | 3/13 [00:00<00:00, 84.92it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  31%|███       | 4/13 [00:00<00:00, 85.90it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  31%|███       | 4/13 [00:00<00:00, 85.53it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  38%|███▊      | 5/13 [00:00<00:00, 85.79it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  38%|███▊      | 5/13 [00:00<00:00, 85.49it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  46%|████▌     | 6/13 [00:00<00:00, 85.68it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  46%|████▌     | 6/13 [00:00<00:00, 85.40it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  54%|█████▍    | 7/13 [00:00<00:00, 85.64it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  54%|█████▍    | 7/13 [00:00<00:00, 85.42it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  62%|██████▏   | 8/13 [00:00<00:00, 85.38it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  62%|██████▏   | 8/13 [00:00<00:00, 85.19it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  69%|██████▉   | 9/13 [00:00<00:00, 84.99it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  69%|██████▉   | 9/13 [00:00<00:00, 84.81it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  77%|███████▋  | 10/13 [00:00<00:00, 84.77it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  77%|███████▋  | 10/13 [00:00<00:00, 84.60it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  85%|████████▍ | 11/13 [00:00<00:00, 84.86it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  85%|████████▍ | 11/13 [00:00<00:00, 84.69it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  92%|█████████▏| 12/13 [00:00<00:00, 84.78it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1:  92%|█████████▏| 12/13 [00:00<00:00, 84.65it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 85.16it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 85.05it/s, v_num=ld_4, val_loss=0.661, train_loss=0.668]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 77.12it/s, v_num=ld_4, val_loss=0.627, train_loss=0.668]
    Epoch 1: 100%|██████████| 13/13 [00:00<00:00, 76.86it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 1:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]         
    Epoch 2:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:   8%|▊         | 1/13 [00:00<00:00, 81.53it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:   8%|▊         | 1/13 [00:00<00:00, 80.01it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  15%|█▌        | 2/13 [00:00<00:00, 83.36it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  15%|█▌        | 2/13 [00:00<00:00, 82.66it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  23%|██▎       | 3/13 [00:00<00:00, 84.19it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  23%|██▎       | 3/13 [00:00<00:00, 83.71it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  31%|███       | 4/13 [00:00<00:00, 83.65it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  31%|███       | 4/13 [00:00<00:00, 83.28it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  38%|███▊      | 5/13 [00:00<00:00, 83.74it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  38%|███▊      | 5/13 [00:00<00:00, 83.45it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  46%|████▌     | 6/13 [00:00<00:00, 83.60it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  46%|████▌     | 6/13 [00:00<00:00, 83.34it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  54%|█████▍    | 7/13 [00:00<00:00, 83.29it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  54%|█████▍    | 7/13 [00:00<00:00, 83.01it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  62%|██████▏   | 8/13 [00:00<00:00, 83.19it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  62%|██████▏   | 8/13 [00:00<00:00, 82.99it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  69%|██████▉   | 9/13 [00:00<00:00, 83.35it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  69%|██████▉   | 9/13 [00:00<00:00, 83.19it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  77%|███████▋  | 10/13 [00:00<00:00, 83.59it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  77%|███████▋  | 10/13 [00:00<00:00, 83.45it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  85%|████████▍ | 11/13 [00:00<00:00, 83.78it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  85%|████████▍ | 11/13 [00:00<00:00, 83.62it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  92%|█████████▏| 12/13 [00:00<00:00, 83.87it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2:  92%|█████████▏| 12/13 [00:00<00:00, 83.74it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 83.94it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 83.82it/s, v_num=ld_4, val_loss=0.627, train_loss=0.594]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 76.29it/s, v_num=ld_4, val_loss=0.604, train_loss=0.594]
    Epoch 2: 100%|██████████| 13/13 [00:00<00:00, 76.03it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 2:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]         
    Epoch 3:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:   8%|▊         | 1/13 [00:00<00:00, 86.17it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:   8%|▊         | 1/13 [00:00<00:00, 84.55it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  15%|█▌        | 2/13 [00:00<00:00, 86.15it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  15%|█▌        | 2/13 [00:00<00:00, 85.39it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  23%|██▎       | 3/13 [00:00<00:00, 86.65it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  23%|██▎       | 3/13 [00:00<00:00, 86.09it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  31%|███       | 4/13 [00:00<00:00, 86.98it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  31%|███       | 4/13 [00:00<00:00, 86.60it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  38%|███▊      | 5/13 [00:00<00:00, 86.26it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  38%|███▊      | 5/13 [00:00<00:00, 85.95it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  46%|████▌     | 6/13 [00:00<00:00, 86.44it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  46%|████▌     | 6/13 [00:00<00:00, 86.17it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  54%|█████▍    | 7/13 [00:00<00:00, 86.53it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  54%|█████▍    | 7/13 [00:00<00:00, 86.31it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  62%|██████▏   | 8/13 [00:00<00:00, 86.67it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  62%|██████▏   | 8/13 [00:00<00:00, 86.47it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  69%|██████▉   | 9/13 [00:00<00:00, 86.81it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  69%|██████▉   | 9/13 [00:00<00:00, 86.62it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  77%|███████▋  | 10/13 [00:00<00:00, 86.96it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  77%|███████▋  | 10/13 [00:00<00:00, 86.80it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  85%|████████▍ | 11/13 [00:00<00:00, 86.59it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  85%|████████▍ | 11/13 [00:00<00:00, 86.44it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  92%|█████████▏| 12/13 [00:00<00:00, 86.57it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3:  92%|█████████▏| 12/13 [00:00<00:00, 86.43it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 86.85it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 86.72it/s, v_num=ld_4, val_loss=0.604, train_loss=0.617]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 78.61it/s, v_num=ld_4, val_loss=0.602, train_loss=0.617]
    Epoch 3: 100%|██████████| 13/13 [00:00<00:00, 78.32it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 3:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]         
    Epoch 4:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:   8%|▊         | 1/13 [00:00<00:00, 85.61it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:   8%|▊         | 1/13 [00:00<00:00, 84.14it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  15%|█▌        | 2/13 [00:00<00:00, 84.50it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  15%|█▌        | 2/13 [00:00<00:00, 83.77it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  23%|██▎       | 3/13 [00:00<00:00, 83.21it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  23%|██▎       | 3/13 [00:00<00:00, 82.67it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  31%|███       | 4/13 [00:00<00:00, 83.55it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  31%|███       | 4/13 [00:00<00:00, 83.20it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  38%|███▊      | 5/13 [00:00<00:00, 83.60it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  38%|███▊      | 5/13 [00:00<00:00, 83.32it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  46%|████▌     | 6/13 [00:00<00:00, 84.14it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  46%|████▌     | 6/13 [00:00<00:00, 83.90it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  54%|█████▍    | 7/13 [00:00<00:00, 84.13it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  54%|█████▍    | 7/13 [00:00<00:00, 83.92it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  62%|██████▏   | 8/13 [00:00<00:00, 84.24it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  62%|██████▏   | 8/13 [00:00<00:00, 84.04it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  69%|██████▉   | 9/13 [00:00<00:00, 84.19it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  69%|██████▉   | 9/13 [00:00<00:00, 83.99it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  77%|███████▋  | 10/13 [00:00<00:00, 84.46it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  77%|███████▋  | 10/13 [00:00<00:00, 84.32it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  85%|████████▍ | 11/13 [00:00<00:00, 84.79it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  85%|████████▍ | 11/13 [00:00<00:00, 84.65it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  92%|█████████▏| 12/13 [00:00<00:00, 85.02it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4:  92%|█████████▏| 12/13 [00:00<00:00, 84.89it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 85.42it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 85.31it/s, v_num=ld_4, val_loss=0.602, train_loss=0.566]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 77.62it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 4: 100%|██████████| 13/13 [00:00<00:00, 77.35it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 4:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]         
    Epoch 5:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:   8%|▊         | 1/13 [00:00<00:00, 81.95it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:   8%|▊         | 1/13 [00:00<00:00, 80.42it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  15%|█▌        | 2/13 [00:00<00:00, 84.16it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  15%|█▌        | 2/13 [00:00<00:00, 83.45it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  23%|██▎       | 3/13 [00:00<00:00, 85.14it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  23%|██▎       | 3/13 [00:00<00:00, 84.60it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  31%|███       | 4/13 [00:00<00:00, 85.10it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  31%|███       | 4/13 [00:00<00:00, 84.73it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  38%|███▊      | 5/13 [00:00<00:00, 85.44it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  38%|███▊      | 5/13 [00:00<00:00, 85.15it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  46%|████▌     | 6/13 [00:00<00:00, 85.62it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  46%|████▌     | 6/13 [00:00<00:00, 85.35it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  54%|█████▍    | 7/13 [00:00<00:00, 85.23it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  54%|█████▍    | 7/13 [00:00<00:00, 84.98it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  62%|██████▏   | 8/13 [00:00<00:00, 85.39it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  62%|██████▏   | 8/13 [00:00<00:00, 85.21it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  69%|██████▉   | 9/13 [00:00<00:00, 85.30it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  69%|██████▉   | 9/13 [00:00<00:00, 85.13it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  77%|███████▋  | 10/13 [00:00<00:00, 85.27it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  77%|███████▋  | 10/13 [00:00<00:00, 85.11it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  85%|████████▍ | 11/13 [00:00<00:00, 85.03it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  85%|████████▍ | 11/13 [00:00<00:00, 84.88it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  92%|█████████▏| 12/13 [00:00<00:00, 85.08it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5:  92%|█████████▏| 12/13 [00:00<00:00, 84.96it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 85.21it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 85.09it/s, v_num=ld_4, val_loss=0.629, train_loss=0.566]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 77.36it/s, v_num=ld_4, val_loss=0.596, train_loss=0.566]
    Epoch 5: 100%|██████████| 13/13 [00:00<00:00, 77.08it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 5:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]         
    Epoch 6:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:   8%|▊         | 1/13 [00:00<00:00, 86.19it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:   8%|▊         | 1/13 [00:00<00:00, 84.70it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  15%|█▌        | 2/13 [00:00<00:00, 86.76it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  15%|█▌        | 2/13 [00:00<00:00, 85.92it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  23%|██▎       | 3/13 [00:00<00:00, 85.43it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  23%|██▎       | 3/13 [00:00<00:00, 84.93it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  31%|███       | 4/13 [00:00<00:00, 85.44it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  31%|███       | 4/13 [00:00<00:00, 85.07it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  38%|███▊      | 5/13 [00:00<00:00, 84.68it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  38%|███▊      | 5/13 [00:00<00:00, 84.36it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  46%|████▌     | 6/13 [00:00<00:00, 84.23it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  46%|████▌     | 6/13 [00:00<00:00, 83.98it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  54%|█████▍    | 7/13 [00:00<00:00, 84.18it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  54%|█████▍    | 7/13 [00:00<00:00, 83.97it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  62%|██████▏   | 8/13 [00:00<00:00, 84.25it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  62%|██████▏   | 8/13 [00:00<00:00, 84.05it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  69%|██████▉   | 9/13 [00:00<00:00, 84.61it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  69%|██████▉   | 9/13 [00:00<00:00, 84.45it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  77%|███████▋  | 10/13 [00:00<00:00, 84.92it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  77%|███████▋  | 10/13 [00:00<00:00, 84.78it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  85%|████████▍ | 11/13 [00:00<00:00, 84.60it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  85%|████████▍ | 11/13 [00:00<00:00, 84.44it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  92%|█████████▏| 12/13 [00:00<00:00, 84.67it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6:  92%|█████████▏| 12/13 [00:00<00:00, 84.54it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 85.05it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 84.93it/s, v_num=ld_4, val_loss=0.596, train_loss=0.553]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 77.15it/s, v_num=ld_4, val_loss=0.595, train_loss=0.553]
    Epoch 6: 100%|██████████| 13/13 [00:00<00:00, 76.86it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 6:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]         
    Epoch 7:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:   8%|▊         | 1/13 [00:00<00:00, 81.84it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:   8%|▊         | 1/13 [00:00<00:00, 80.18it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  15%|█▌        | 2/13 [00:00<00:00, 81.96it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  15%|█▌        | 2/13 [00:00<00:00, 81.21it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  23%|██▎       | 3/13 [00:00<00:00, 80.68it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  23%|██▎       | 3/13 [00:00<00:00, 80.14it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  31%|███       | 4/13 [00:00<00:00, 80.79it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  31%|███       | 4/13 [00:00<00:00, 80.46it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  38%|███▊      | 5/13 [00:00<00:00, 81.17it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  38%|███▊      | 5/13 [00:00<00:00, 80.90it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  46%|████▌     | 6/13 [00:00<00:00, 81.39it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  46%|████▌     | 6/13 [00:00<00:00, 81.17it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  54%|█████▍    | 7/13 [00:00<00:00, 81.95it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  54%|█████▍    | 7/13 [00:00<00:00, 81.75it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  62%|██████▏   | 8/13 [00:00<00:00, 82.13it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  62%|██████▏   | 8/13 [00:00<00:00, 81.96it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  69%|██████▉   | 9/13 [00:00<00:00, 82.14it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  69%|██████▉   | 9/13 [00:00<00:00, 81.97it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  77%|███████▋  | 10/13 [00:00<00:00, 82.39it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  77%|███████▋  | 10/13 [00:00<00:00, 82.26it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  85%|████████▍ | 11/13 [00:00<00:00, 82.73it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  85%|████████▍ | 11/13 [00:00<00:00, 82.60it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  92%|█████████▏| 12/13 [00:00<00:00, 83.09it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7:  92%|█████████▏| 12/13 [00:00<00:00, 82.97it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 83.69it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 83.58it/s, v_num=ld_4, val_loss=0.595, train_loss=0.548]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 76.12it/s, v_num=ld_4, val_loss=0.580, train_loss=0.548]
    Epoch 7: 100%|██████████| 13/13 [00:00<00:00, 75.85it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 7:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]         
    Epoch 8:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:   8%|▊         | 1/13 [00:00<00:00, 79.74it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:   8%|▊         | 1/13 [00:00<00:00, 78.33it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  15%|█▌        | 2/13 [00:00<00:00, 83.20it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  15%|█▌        | 2/13 [00:00<00:00, 82.42it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  23%|██▎       | 3/13 [00:00<00:00, 83.29it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  23%|██▎       | 3/13 [00:00<00:00, 82.78it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  31%|███       | 4/13 [00:00<00:00, 83.85it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  31%|███       | 4/13 [00:00<00:00, 83.50it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  38%|███▊      | 5/13 [00:00<00:00, 84.25it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  38%|███▊      | 5/13 [00:00<00:00, 83.96it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  46%|████▌     | 6/13 [00:00<00:00, 84.66it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  46%|████▌     | 6/13 [00:00<00:00, 84.42it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  54%|█████▍    | 7/13 [00:00<00:00, 84.33it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  54%|█████▍    | 7/13 [00:00<00:00, 84.08it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  62%|██████▏   | 8/13 [00:00<00:00, 84.38it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  62%|██████▏   | 8/13 [00:00<00:00, 84.20it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  69%|██████▉   | 9/13 [00:00<00:00, 84.78it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  69%|██████▉   | 9/13 [00:00<00:00, 84.60it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  77%|███████▋  | 10/13 [00:00<00:00, 85.01it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  77%|███████▋  | 10/13 [00:00<00:00, 84.86it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  85%|████████▍ | 11/13 [00:00<00:00, 85.10it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  85%|████████▍ | 11/13 [00:00<00:00, 84.97it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  92%|█████████▏| 12/13 [00:00<00:00, 85.12it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8:  92%|█████████▏| 12/13 [00:00<00:00, 84.99it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 85.23it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 85.10it/s, v_num=ld_4, val_loss=0.580, train_loss=0.537]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 77.42it/s, v_num=ld_4, val_loss=0.579, train_loss=0.537]
    Epoch 8: 100%|██████████| 13/13 [00:00<00:00, 77.14it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 8:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]         
    Epoch 9:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:   8%|▊         | 1/13 [00:00<00:00, 84.66it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:   8%|▊         | 1/13 [00:00<00:00, 83.23it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  15%|█▌        | 2/13 [00:00<00:00, 84.83it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  15%|█▌        | 2/13 [00:00<00:00, 84.11it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  23%|██▎       | 3/13 [00:00<00:00, 85.86it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  23%|██▎       | 3/13 [00:00<00:00, 85.31it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  31%|███       | 4/13 [00:00<00:00, 85.90it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  31%|███       | 4/13 [00:00<00:00, 85.52it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  38%|███▊      | 5/13 [00:00<00:00, 85.43it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  38%|███▊      | 5/13 [00:00<00:00, 85.10it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  46%|████▌     | 6/13 [00:00<00:00, 85.59it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  46%|████▌     | 6/13 [00:00<00:00, 85.34it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  54%|█████▍    | 7/13 [00:00<00:00, 85.58it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  54%|█████▍    | 7/13 [00:00<00:00, 85.35it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  62%|██████▏   | 8/13 [00:00<00:00, 85.64it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  62%|██████▏   | 8/13 [00:00<00:00, 85.45it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  69%|██████▉   | 9/13 [00:00<00:00, 85.68it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  69%|██████▉   | 9/13 [00:00<00:00, 85.49it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  77%|███████▋  | 10/13 [00:00<00:00, 85.73it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  77%|███████▋  | 10/13 [00:00<00:00, 85.57it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  85%|████████▍ | 11/13 [00:00<00:00, 85.41it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  85%|████████▍ | 11/13 [00:00<00:00, 85.26it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  92%|█████████▏| 12/13 [00:00<00:00, 85.51it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9:  92%|█████████▏| 12/13 [00:00<00:00, 85.39it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 85.93it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 85.82it/s, v_num=ld_4, val_loss=0.579, train_loss=0.532]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 77.93it/s, v_num=ld_4, val_loss=0.592, train_loss=0.532]
    Epoch 9: 100%|██████████| 13/13 [00:00<00:00, 77.65it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 9:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]         
    Epoch 10:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:   8%|▊         | 1/13 [00:00<00:00, 86.54it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:   8%|▊         | 1/13 [00:00<00:00, 85.05it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  15%|█▌        | 2/13 [00:00<00:00, 86.05it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  15%|█▌        | 2/13 [00:00<00:00, 85.31it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  23%|██▎       | 3/13 [00:00<00:00, 84.59it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  23%|██▎       | 3/13 [00:00<00:00, 84.06it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  31%|███       | 4/13 [00:00<00:00, 83.63it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  31%|███       | 4/13 [00:00<00:00, 83.28it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  38%|███▊      | 5/13 [00:00<00:00, 84.06it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  38%|███▊      | 5/13 [00:00<00:00, 83.77it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  46%|████▌     | 6/13 [00:00<00:00, 84.46it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  46%|████▌     | 6/13 [00:00<00:00, 84.19it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  54%|█████▍    | 7/13 [00:00<00:00, 84.68it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  54%|█████▍    | 7/13 [00:00<00:00, 84.47it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  62%|██████▏   | 8/13 [00:00<00:00, 84.71it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  62%|██████▏   | 8/13 [00:00<00:00, 84.53it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  69%|██████▉   | 9/13 [00:00<00:00, 84.45it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  69%|██████▉   | 9/13 [00:00<00:00, 84.28it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  77%|███████▋  | 10/13 [00:00<00:00, 84.63it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  77%|███████▋  | 10/13 [00:00<00:00, 84.48it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  85%|████████▍ | 11/13 [00:00<00:00, 84.83it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  85%|████████▍ | 11/13 [00:00<00:00, 84.70it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  92%|█████████▏| 12/13 [00:00<00:00, 84.61it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10:  92%|█████████▏| 12/13 [00:00<00:00, 84.48it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 84.95it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 84.83it/s, v_num=ld_4, val_loss=0.592, train_loss=0.529]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 77.16it/s, v_num=ld_4, val_loss=0.600, train_loss=0.529]
    Epoch 10: 100%|██████████| 13/13 [00:00<00:00, 76.88it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 10:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]         
    Epoch 11:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:   8%|▊         | 1/13 [00:00<00:00, 78.89it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:   8%|▊         | 1/13 [00:00<00:00, 77.55it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  15%|█▌        | 2/13 [00:00<00:00, 81.17it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  15%|█▌        | 2/13 [00:00<00:00, 80.50it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  23%|██▎       | 3/13 [00:00<00:00, 81.23it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  23%|██▎       | 3/13 [00:00<00:00, 80.77it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  31%|███       | 4/13 [00:00<00:00, 81.58it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  31%|███       | 4/13 [00:00<00:00, 81.24it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  38%|███▊      | 5/13 [00:00<00:00, 82.56it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  38%|███▊      | 5/13 [00:00<00:00, 82.28it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  46%|████▌     | 6/13 [00:00<00:00, 82.20it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  46%|████▌     | 6/13 [00:00<00:00, 81.97it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  54%|█████▍    | 7/13 [00:00<00:00, 81.39it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  54%|█████▍    | 7/13 [00:00<00:00, 81.19it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  62%|██████▏   | 8/13 [00:00<00:00, 81.56it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  62%|██████▏   | 8/13 [00:00<00:00, 81.39it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  69%|██████▉   | 9/13 [00:00<00:00, 81.86it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  69%|██████▉   | 9/13 [00:00<00:00, 81.71it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  77%|███████▋  | 10/13 [00:00<00:00, 82.24it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  77%|███████▋  | 10/13 [00:00<00:00, 82.10it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  85%|████████▍ | 11/13 [00:00<00:00, 82.54it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  85%|████████▍ | 11/13 [00:00<00:00, 82.40it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  92%|█████████▏| 12/13 [00:00<00:00, 82.70it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11:  92%|█████████▏| 12/13 [00:00<00:00, 82.59it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 82.91it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 82.79it/s, v_num=ld_4, val_loss=0.600, train_loss=0.535]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 75.28it/s, v_num=ld_4, val_loss=0.605, train_loss=0.535]
    Epoch 11: 100%|██████████| 13/13 [00:00<00:00, 74.94it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 11:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]         
    Epoch 12:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:   8%|▊         | 1/13 [00:00<00:00, 84.42it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:   8%|▊         | 1/13 [00:00<00:00, 82.98it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  15%|█▌        | 2/13 [00:00<00:00, 84.70it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  15%|█▌        | 2/13 [00:00<00:00, 83.97it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  23%|██▎       | 3/13 [00:00<00:00, 84.47it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  23%|██▎       | 3/13 [00:00<00:00, 83.98it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  31%|███       | 4/13 [00:00<00:00, 84.88it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  31%|███       | 4/13 [00:00<00:00, 84.47it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  38%|███▊      | 5/13 [00:00<00:00, 84.27it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  38%|███▊      | 5/13 [00:00<00:00, 83.96it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  46%|████▌     | 6/13 [00:00<00:00, 84.51it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  46%|████▌     | 6/13 [00:00<00:00, 84.27it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  54%|█████▍    | 7/13 [00:00<00:00, 84.81it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  54%|█████▍    | 7/13 [00:00<00:00, 84.60it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  62%|██████▏   | 8/13 [00:00<00:00, 84.81it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  62%|██████▏   | 8/13 [00:00<00:00, 84.63it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  69%|██████▉   | 9/13 [00:00<00:00, 85.06it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  69%|██████▉   | 9/13 [00:00<00:00, 84.90it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  77%|███████▋  | 10/13 [00:00<00:00, 85.33it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  77%|███████▋  | 10/13 [00:00<00:00, 85.17it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  85%|████████▍ | 11/13 [00:00<00:00, 85.18it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  85%|████████▍ | 11/13 [00:00<00:00, 85.02it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  92%|█████████▏| 12/13 [00:00<00:00, 85.26it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12:  92%|█████████▏| 12/13 [00:00<00:00, 85.14it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 85.66it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 85.54it/s, v_num=ld_4, val_loss=0.605, train_loss=0.540]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 77.75it/s, v_num=ld_4, val_loss=0.590, train_loss=0.540]
    Epoch 12: 100%|██████████| 13/13 [00:00<00:00, 77.47it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 12:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]         
    Epoch 13:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:   8%|▊         | 1/13 [00:00<00:00, 87.51it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:   8%|▊         | 1/13 [00:00<00:00, 85.97it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  15%|█▌        | 2/13 [00:00<00:00, 86.77it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  15%|█▌        | 2/13 [00:00<00:00, 86.01it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  23%|██▎       | 3/13 [00:00<00:00, 84.60it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  23%|██▎       | 3/13 [00:00<00:00, 84.07it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  31%|███       | 4/13 [00:00<00:00, 84.61it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  31%|███       | 4/13 [00:00<00:00, 84.25it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  38%|███▊      | 5/13 [00:00<00:00, 84.12it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  38%|███▊      | 5/13 [00:00<00:00, 83.81it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  46%|████▌     | 6/13 [00:00<00:00, 83.88it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  46%|████▌     | 6/13 [00:00<00:00, 83.62it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  54%|█████▍    | 7/13 [00:00<00:00, 83.78it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  54%|█████▍    | 7/13 [00:00<00:00, 83.56it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  62%|██████▏   | 8/13 [00:00<00:00, 83.65it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  62%|██████▏   | 8/13 [00:00<00:00, 83.45it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  69%|██████▉   | 9/13 [00:00<00:00, 83.05it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  69%|██████▉   | 9/13 [00:00<00:00, 82.88it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  77%|███████▋  | 10/13 [00:00<00:00, 83.03it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  77%|███████▋  | 10/13 [00:00<00:00, 82.88it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  85%|████████▍ | 11/13 [00:00<00:00, 82.94it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  85%|████████▍ | 11/13 [00:00<00:00, 82.81it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  92%|█████████▏| 12/13 [00:00<00:00, 82.81it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13:  92%|█████████▏| 12/13 [00:00<00:00, 82.69it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 83.29it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 83.17it/s, v_num=ld_4, val_loss=0.590, train_loss=0.528]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 75.57it/s, v_num=ld_4, val_loss=0.575, train_loss=0.528]
    Epoch 13: 100%|██████████| 13/13 [00:00<00:00, 75.31it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 13:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]         
    Epoch 14:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:   8%|▊         | 1/13 [00:00<00:00, 80.05it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:   8%|▊         | 1/13 [00:00<00:00, 78.57it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  15%|█▌        | 2/13 [00:00<00:00, 82.82it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  15%|█▌        | 2/13 [00:00<00:00, 82.11it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  23%|██▎       | 3/13 [00:00<00:00, 83.29it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  23%|██▎       | 3/13 [00:00<00:00, 82.82it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  31%|███       | 4/13 [00:00<00:00, 83.14it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  31%|███       | 4/13 [00:00<00:00, 82.79it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  38%|███▊      | 5/13 [00:00<00:00, 83.48it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  38%|███▊      | 5/13 [00:00<00:00, 83.19it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  46%|████▌     | 6/13 [00:00<00:00, 83.76it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  46%|████▌     | 6/13 [00:00<00:00, 83.53it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  54%|█████▍    | 7/13 [00:00<00:00, 83.81it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  54%|█████▍    | 7/13 [00:00<00:00, 83.58it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  62%|██████▏   | 8/13 [00:00<00:00, 84.26it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  62%|██████▏   | 8/13 [00:00<00:00, 84.08it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  69%|██████▉   | 9/13 [00:00<00:00, 84.72it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  69%|██████▉   | 9/13 [00:00<00:00, 84.56it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  77%|███████▋  | 10/13 [00:00<00:00, 85.10it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  77%|███████▋  | 10/13 [00:00<00:00, 84.94it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  85%|████████▍ | 11/13 [00:00<00:00, 85.34it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  85%|████████▍ | 11/13 [00:00<00:00, 85.21it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  92%|█████████▏| 12/13 [00:00<00:00, 85.55it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14:  92%|█████████▏| 12/13 [00:00<00:00, 85.42it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 85.56it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 85.44it/s, v_num=ld_4, val_loss=0.575, train_loss=0.538]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 77.69it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 14: 100%|██████████| 13/13 [00:00<00:00, 77.41it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 14:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]         
    Epoch 15:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:   8%|▊         | 1/13 [00:00<00:00, 89.05it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:   8%|▊         | 1/13 [00:00<00:00, 87.47it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  15%|█▌        | 2/13 [00:00<00:00, 88.55it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  15%|█▌        | 2/13 [00:00<00:00, 87.75it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  23%|██▎       | 3/13 [00:00<00:00, 88.28it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  23%|██▎       | 3/13 [00:00<00:00, 87.75it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  31%|███       | 4/13 [00:00<00:00, 88.27it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  31%|███       | 4/13 [00:00<00:00, 87.87it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  38%|███▊      | 5/13 [00:00<00:00, 87.43it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  38%|███▊      | 5/13 [00:00<00:00, 87.09it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  46%|████▌     | 6/13 [00:00<00:00, 87.35it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  46%|████▌     | 6/13 [00:00<00:00, 87.09it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  54%|█████▍    | 7/13 [00:00<00:00, 87.13it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  54%|█████▍    | 7/13 [00:00<00:00, 86.90it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  62%|██████▏   | 8/13 [00:00<00:00, 87.35it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  62%|██████▏   | 8/13 [00:00<00:00, 87.15it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  69%|██████▉   | 9/13 [00:00<00:00, 87.47it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  69%|██████▉   | 9/13 [00:00<00:00, 87.28it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  77%|███████▋  | 10/13 [00:00<00:00, 87.47it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  77%|███████▋  | 10/13 [00:00<00:00, 87.31it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  85%|████████▍ | 11/13 [00:00<00:00, 87.17it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  85%|████████▍ | 11/13 [00:00<00:00, 87.01it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  92%|█████████▏| 12/13 [00:00<00:00, 87.18it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15:  92%|█████████▏| 12/13 [00:00<00:00, 87.05it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 87.59it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 87.47it/s, v_num=ld_4, val_loss=0.632, train_loss=0.530]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 79.43it/s, v_num=ld_4, val_loss=0.617, train_loss=0.530]
    Epoch 15: 100%|██████████| 13/13 [00:00<00:00, 79.13it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 15:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]         
    Epoch 16:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:   8%|▊         | 1/13 [00:00<00:00, 87.68it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:   8%|▊         | 1/13 [00:00<00:00, 86.15it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  15%|█▌        | 2/13 [00:00<00:00, 88.14it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  15%|█▌        | 2/13 [00:00<00:00, 87.36it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  23%|██▎       | 3/13 [00:00<00:00, 86.77it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  23%|██▎       | 3/13 [00:00<00:00, 86.20it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  31%|███       | 4/13 [00:00<00:00, 86.75it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  31%|███       | 4/13 [00:00<00:00, 86.37it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  38%|███▊      | 5/13 [00:00<00:00, 86.85it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  38%|███▊      | 5/13 [00:00<00:00, 86.54it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  46%|████▌     | 6/13 [00:00<00:00, 86.86it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  46%|████▌     | 6/13 [00:00<00:00, 86.60it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  54%|█████▍    | 7/13 [00:00<00:00, 86.94it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  54%|█████▍    | 7/13 [00:00<00:00, 86.72it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  62%|██████▏   | 8/13 [00:00<00:00, 87.05it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  62%|██████▏   | 8/13 [00:00<00:00, 86.84it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  69%|██████▉   | 9/13 [00:00<00:00, 86.53it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  69%|██████▉   | 9/13 [00:00<00:00, 86.33it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  77%|███████▋  | 10/13 [00:00<00:00, 86.46it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  77%|███████▋  | 10/13 [00:00<00:00, 86.31it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  85%|████████▍ | 11/13 [00:00<00:00, 86.29it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  85%|████████▍ | 11/13 [00:00<00:00, 86.15it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  92%|█████████▏| 12/13 [00:00<00:00, 86.23it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16:  92%|█████████▏| 12/13 [00:00<00:00, 86.10it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 86.60it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 86.48it/s, v_num=ld_4, val_loss=0.617, train_loss=0.532]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 78.54it/s, v_num=ld_4, val_loss=0.592, train_loss=0.532]
    Epoch 16: 100%|██████████| 13/13 [00:00<00:00, 78.26it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 16:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]         
    Epoch 17:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:   8%|▊         | 1/13 [00:00<00:00, 82.32it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:   8%|▊         | 1/13 [00:00<00:00, 80.71it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  15%|█▌        | 2/13 [00:00<00:00, 84.14it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  15%|█▌        | 2/13 [00:00<00:00, 83.42it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  23%|██▎       | 3/13 [00:00<00:00, 84.92it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  23%|██▎       | 3/13 [00:00<00:00, 84.38it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  31%|███       | 4/13 [00:00<00:00, 85.27it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  31%|███       | 4/13 [00:00<00:00, 84.90it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  38%|███▊      | 5/13 [00:00<00:00, 85.48it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  38%|███▊      | 5/13 [00:00<00:00, 85.18it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  46%|████▌     | 6/13 [00:00<00:00, 85.85it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  46%|████▌     | 6/13 [00:00<00:00, 85.60it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  54%|█████▍    | 7/13 [00:00<00:00, 85.32it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  54%|█████▍    | 7/13 [00:00<00:00, 85.03it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  62%|██████▏   | 8/13 [00:00<00:00, 85.06it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  62%|██████▏   | 8/13 [00:00<00:00, 84.88it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  69%|██████▉   | 9/13 [00:00<00:00, 84.84it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  69%|██████▉   | 9/13 [00:00<00:00, 84.67it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  77%|███████▋  | 10/13 [00:00<00:00, 84.92it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  77%|███████▋  | 10/13 [00:00<00:00, 84.78it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  85%|████████▍ | 11/13 [00:00<00:00, 85.08it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  85%|████████▍ | 11/13 [00:00<00:00, 84.93it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  92%|█████████▏| 12/13 [00:00<00:00, 85.17it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17:  92%|█████████▏| 12/13 [00:00<00:00, 85.05it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 85.24it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 85.12it/s, v_num=ld_4, val_loss=0.592, train_loss=0.525]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 77.45it/s, v_num=ld_4, val_loss=0.645, train_loss=0.525]
    Epoch 17: 100%|██████████| 13/13 [00:00<00:00, 77.17it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 17:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]         
    Epoch 18:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:   8%|▊         | 1/13 [00:00<00:00, 85.47it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:   8%|▊         | 1/13 [00:00<00:00, 84.00it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  15%|█▌        | 2/13 [00:00<00:00, 84.42it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  15%|█▌        | 2/13 [00:00<00:00, 83.65it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  23%|██▎       | 3/13 [00:00<00:00, 84.26it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  23%|██▎       | 3/13 [00:00<00:00, 83.78it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  31%|███       | 4/13 [00:00<00:00, 84.84it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  31%|███       | 4/13 [00:00<00:00, 84.44it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  38%|███▊      | 5/13 [00:00<00:00, 84.03it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  38%|███▊      | 5/13 [00:00<00:00, 83.72it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  46%|████▌     | 6/13 [00:00<00:00, 84.29it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  46%|████▌     | 6/13 [00:00<00:00, 84.02it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  54%|█████▍    | 7/13 [00:00<00:00, 84.54it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  54%|█████▍    | 7/13 [00:00<00:00, 84.33it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  62%|██████▏   | 8/13 [00:00<00:00, 84.80it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  62%|██████▏   | 8/13 [00:00<00:00, 84.62it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  69%|██████▉   | 9/13 [00:00<00:00, 84.89it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  69%|██████▉   | 9/13 [00:00<00:00, 84.73it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  77%|███████▋  | 10/13 [00:00<00:00, 84.97it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  77%|███████▋  | 10/13 [00:00<00:00, 84.83it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  85%|████████▍ | 11/13 [00:00<00:00, 84.76it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  85%|████████▍ | 11/13 [00:00<00:00, 84.61it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  92%|█████████▏| 12/13 [00:00<00:00, 84.85it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18:  92%|█████████▏| 12/13 [00:00<00:00, 84.73it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 85.32it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 85.21it/s, v_num=ld_4, val_loss=0.645, train_loss=0.542]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 77.51it/s, v_num=ld_4, val_loss=0.619, train_loss=0.542]
    Epoch 18: 100%|██████████| 13/13 [00:00<00:00, 77.23it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 18:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]         
    Epoch 19:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:   8%|▊         | 1/13 [00:00<00:00, 83.98it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:   8%|▊         | 1/13 [00:00<00:00, 82.56it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  15%|█▌        | 2/13 [00:00<00:00, 84.63it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  15%|█▌        | 2/13 [00:00<00:00, 83.90it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  23%|██▎       | 3/13 [00:00<00:00, 83.36it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  23%|██▎       | 3/13 [00:00<00:00, 82.88it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  31%|███       | 4/13 [00:00<00:00, 83.97it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  31%|███       | 4/13 [00:00<00:00, 83.61it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  38%|███▊      | 5/13 [00:00<00:00, 84.23it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  38%|███▊      | 5/13 [00:00<00:00, 83.94it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  46%|████▌     | 6/13 [00:00<00:00, 84.39it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  46%|████▌     | 6/13 [00:00<00:00, 84.14it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  54%|█████▍    | 7/13 [00:00<00:00, 84.60it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  54%|█████▍    | 7/13 [00:00<00:00, 84.40it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  62%|██████▏   | 8/13 [00:00<00:00, 84.67it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  62%|██████▏   | 8/13 [00:00<00:00, 84.48it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  69%|██████▉   | 9/13 [00:00<00:00, 84.31it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  69%|██████▉   | 9/13 [00:00<00:00, 84.13it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  77%|███████▋  | 10/13 [00:00<00:00, 84.42it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  77%|███████▋  | 10/13 [00:00<00:00, 84.27it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  85%|████████▍ | 11/13 [00:00<00:00, 84.49it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  85%|████████▍ | 11/13 [00:00<00:00, 84.33it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  92%|█████████▏| 12/13 [00:00<00:00, 84.56it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19:  92%|█████████▏| 12/13 [00:00<00:00, 84.44it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 84.76it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 84.64it/s, v_num=ld_4, val_loss=0.619, train_loss=0.540]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 76.85it/s, v_num=ld_4, val_loss=0.632, train_loss=0.540]
    Epoch 19: 100%|██████████| 13/13 [00:00<00:00, 76.57it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 19:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]         
    Epoch 20:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:   8%|▊         | 1/13 [00:00<00:00, 80.02it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:   8%|▊         | 1/13 [00:00<00:00, 78.66it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  15%|█▌        | 2/13 [00:00<00:00, 82.31it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  15%|█▌        | 2/13 [00:00<00:00, 81.58it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  23%|██▎       | 3/13 [00:00<00:00, 83.00it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  23%|██▎       | 3/13 [00:00<00:00, 82.53it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  31%|███       | 4/13 [00:00<00:00, 83.56it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  31%|███       | 4/13 [00:00<00:00, 83.17it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  38%|███▊      | 5/13 [00:00<00:00, 83.99it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  38%|███▊      | 5/13 [00:00<00:00, 83.70it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  46%|████▌     | 6/13 [00:00<00:00, 84.40it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  46%|████▌     | 6/13 [00:00<00:00, 84.16it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  54%|█████▍    | 7/13 [00:00<00:00, 84.10it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  54%|█████▍    | 7/13 [00:00<00:00, 83.87it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  62%|██████▏   | 8/13 [00:00<00:00, 84.08it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  62%|██████▏   | 8/13 [00:00<00:00, 83.90it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  69%|██████▉   | 9/13 [00:00<00:00, 84.32it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  69%|██████▉   | 9/13 [00:00<00:00, 84.14it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  77%|███████▋  | 10/13 [00:00<00:00, 84.55it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  77%|███████▋  | 10/13 [00:00<00:00, 84.40it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  85%|████████▍ | 11/13 [00:00<00:00, 84.03it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  85%|████████▍ | 11/13 [00:00<00:00, 83.88it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  92%|█████████▏| 12/13 [00:00<00:00, 84.26it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20:  92%|█████████▏| 12/13 [00:00<00:00, 84.14it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 84.41it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 84.30it/s, v_num=ld_4, val_loss=0.632, train_loss=0.538]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 76.72it/s, v_num=ld_4, val_loss=0.618, train_loss=0.538]
    Epoch 20: 100%|██████████| 13/13 [00:00<00:00, 76.45it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 20:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]         
    Epoch 21:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:   8%|▊         | 1/13 [00:00<00:00, 86.72it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:   8%|▊         | 1/13 [00:00<00:00, 85.19it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  15%|█▌        | 2/13 [00:00<00:00, 84.80it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  15%|█▌        | 2/13 [00:00<00:00, 84.00it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  23%|██▎       | 3/13 [00:00<00:00, 85.54it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  23%|██▎       | 3/13 [00:00<00:00, 84.99it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  31%|███       | 4/13 [00:00<00:00, 85.83it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  31%|███       | 4/13 [00:00<00:00, 85.46it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  38%|███▊      | 5/13 [00:00<00:00, 85.23it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  38%|███▊      | 5/13 [00:00<00:00, 84.93it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  46%|████▌     | 6/13 [00:00<00:00, 84.88it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  46%|████▌     | 6/13 [00:00<00:00, 84.64it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  54%|█████▍    | 7/13 [00:00<00:00, 85.40it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  54%|█████▍    | 7/13 [00:00<00:00, 85.19it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  62%|██████▏   | 8/13 [00:00<00:00, 85.71it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  62%|██████▏   | 8/13 [00:00<00:00, 85.52it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  69%|██████▉   | 9/13 [00:00<00:00, 86.03it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  69%|██████▉   | 9/13 [00:00<00:00, 85.86it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  77%|███████▋  | 10/13 [00:00<00:00, 85.67it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  77%|███████▋  | 10/13 [00:00<00:00, 85.52it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  85%|████████▍ | 11/13 [00:00<00:00, 85.46it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  85%|████████▍ | 11/13 [00:00<00:00, 85.31it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  92%|█████████▏| 12/13 [00:00<00:00, 85.60it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21:  92%|█████████▏| 12/13 [00:00<00:00, 85.47it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 85.92it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 85.80it/s, v_num=ld_4, val_loss=0.618, train_loss=0.523]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 77.99it/s, v_num=ld_4, val_loss=0.646, train_loss=0.523]
    Epoch 21: 100%|██████████| 13/13 [00:00<00:00, 77.72it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 21:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]         
    Epoch 22:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:   8%|▊         | 1/13 [00:00<00:00, 85.79it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:   8%|▊         | 1/13 [00:00<00:00, 84.32it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  15%|█▌        | 2/13 [00:00<00:00, 86.94it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  15%|█▌        | 2/13 [00:00<00:00, 86.18it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  23%|██▎       | 3/13 [00:00<00:00, 85.81it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  23%|██▎       | 3/13 [00:00<00:00, 85.29it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  31%|███       | 4/13 [00:00<00:00, 86.03it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  31%|███       | 4/13 [00:00<00:00, 85.65it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  38%|███▊      | 5/13 [00:00<00:00, 86.17it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  38%|███▊      | 5/13 [00:00<00:00, 85.87it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  46%|████▌     | 6/13 [00:00<00:00, 86.31it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  46%|████▌     | 6/13 [00:00<00:00, 86.05it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  54%|█████▍    | 7/13 [00:00<00:00, 86.57it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  54%|█████▍    | 7/13 [00:00<00:00, 86.35it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  62%|██████▏   | 8/13 [00:00<00:00, 86.69it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  62%|██████▏   | 8/13 [00:00<00:00, 86.48it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  69%|██████▉   | 9/13 [00:00<00:00, 86.19it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  69%|██████▉   | 9/13 [00:00<00:00, 86.02it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  77%|███████▋  | 10/13 [00:00<00:00, 85.80it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  77%|███████▋  | 10/13 [00:00<00:00, 85.65it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  85%|████████▍ | 11/13 [00:00<00:00, 85.86it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  85%|████████▍ | 11/13 [00:00<00:00, 85.72it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  92%|█████████▏| 12/13 [00:00<00:00, 85.39it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22:  92%|█████████▏| 12/13 [00:00<00:00, 85.27it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 85.74it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 85.62it/s, v_num=ld_4, val_loss=0.646, train_loss=0.539]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 77.57it/s, v_num=ld_4, val_loss=0.625, train_loss=0.539]
    Epoch 22: 100%|██████████| 13/13 [00:00<00:00, 77.30it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 22:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]         
    Epoch 23:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:   8%|▊         | 1/13 [00:00<00:00, 77.84it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:   8%|▊         | 1/13 [00:00<00:00, 76.53it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  15%|█▌        | 2/13 [00:00<00:00, 80.34it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  15%|█▌        | 2/13 [00:00<00:00, 79.68it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  23%|██▎       | 3/13 [00:00<00:00, 81.34it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  23%|██▎       | 3/13 [00:00<00:00, 80.87it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  31%|███       | 4/13 [00:00<00:00, 81.97it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  31%|███       | 4/13 [00:00<00:00, 81.62it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  38%|███▊      | 5/13 [00:00<00:00, 82.66it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  38%|███▊      | 5/13 [00:00<00:00, 82.34it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  46%|████▌     | 6/13 [00:00<00:00, 83.11it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  46%|████▌     | 6/13 [00:00<00:00, 82.88it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  54%|█████▍    | 7/13 [00:00<00:00, 81.52it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  54%|█████▍    | 7/13 [00:00<00:00, 81.31it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  62%|██████▏   | 8/13 [00:00<00:00, 80.89it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  62%|██████▏   | 8/13 [00:00<00:00, 80.73it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  69%|██████▉   | 9/13 [00:00<00:00, 81.17it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  69%|██████▉   | 9/13 [00:00<00:00, 81.02it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  77%|███████▋  | 10/13 [00:00<00:00, 81.07it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  77%|███████▋  | 10/13 [00:00<00:00, 80.94it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  85%|████████▍ | 11/13 [00:00<00:00, 80.97it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  85%|████████▍ | 11/13 [00:00<00:00, 80.85it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  92%|█████████▏| 12/13 [00:00<00:00, 81.10it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23:  92%|█████████▏| 12/13 [00:00<00:00, 80.99it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 81.42it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 81.30it/s, v_num=ld_4, val_loss=0.625, train_loss=0.524]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 74.03it/s, v_num=ld_4, val_loss=0.617, train_loss=0.524]
    Epoch 23: 100%|██████████| 13/13 [00:00<00:00, 73.78it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 23:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]         
    Epoch 24:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:   8%|▊         | 1/13 [00:00<00:00, 83.68it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:   8%|▊         | 1/13 [00:00<00:00, 82.25it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  15%|█▌        | 2/13 [00:00<00:00, 84.97it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  15%|█▌        | 2/13 [00:00<00:00, 84.10it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  23%|██▎       | 3/13 [00:00<00:00, 85.63it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  23%|██▎       | 3/13 [00:00<00:00, 85.13it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  31%|███       | 4/13 [00:00<00:00, 86.06it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  31%|███       | 4/13 [00:00<00:00, 85.68it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  38%|███▊      | 5/13 [00:00<00:00, 84.77it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  38%|███▊      | 5/13 [00:00<00:00, 84.47it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  46%|████▌     | 6/13 [00:00<00:00, 83.68it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  46%|████▌     | 6/13 [00:00<00:00, 83.40it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  54%|█████▍    | 7/13 [00:00<00:00, 83.89it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  54%|█████▍    | 7/13 [00:00<00:00, 83.67it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  62%|██████▏   | 8/13 [00:00<00:00, 84.24it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  62%|██████▏   | 8/13 [00:00<00:00, 84.06it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  69%|██████▉   | 9/13 [00:00<00:00, 84.30it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  69%|██████▉   | 9/13 [00:00<00:00, 84.14it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  77%|███████▋  | 10/13 [00:00<00:00, 83.83it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  77%|███████▋  | 10/13 [00:00<00:00, 83.68it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  85%|████████▍ | 11/13 [00:00<00:00, 83.57it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  85%|████████▍ | 11/13 [00:00<00:00, 83.42it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  92%|█████████▏| 12/13 [00:00<00:00, 83.81it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24:  92%|█████████▏| 12/13 [00:00<00:00, 83.70it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 83.94it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 83.80it/s, v_num=ld_4, val_loss=0.617, train_loss=0.525]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 76.12it/s, v_num=ld_4, val_loss=0.609, train_loss=0.525]
    Epoch 24: 100%|██████████| 13/13 [00:00<00:00, 75.83it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 24:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]         
    Epoch 25:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:   8%|▊         | 1/13 [00:00<00:00, 71.40it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:   8%|▊         | 1/13 [00:00<00:00, 70.21it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  15%|█▌        | 2/13 [00:00<00:00, 71.96it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  15%|█▌        | 2/13 [00:00<00:00, 71.36it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  23%|██▎       | 3/13 [00:00<00:00, 72.01it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  23%|██▎       | 3/13 [00:00<00:00, 71.62it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  31%|███       | 4/13 [00:00<00:00, 71.81it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  31%|███       | 4/13 [00:00<00:00, 71.54it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  38%|███▊      | 5/13 [00:00<00:00, 73.41it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  38%|███▊      | 5/13 [00:00<00:00, 73.18it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  46%|████▌     | 6/13 [00:00<00:00, 74.97it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  46%|████▌     | 6/13 [00:00<00:00, 74.77it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  54%|█████▍    | 7/13 [00:00<00:00, 75.94it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  54%|█████▍    | 7/13 [00:00<00:00, 75.77it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  62%|██████▏   | 8/13 [00:00<00:00, 76.99it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  62%|██████▏   | 8/13 [00:00<00:00, 76.84it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  69%|██████▉   | 9/13 [00:00<00:00, 77.52it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  69%|██████▉   | 9/13 [00:00<00:00, 77.31it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  77%|███████▋  | 10/13 [00:00<00:00, 77.91it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  77%|███████▋  | 10/13 [00:00<00:00, 77.78it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  85%|████████▍ | 11/13 [00:00<00:00, 78.26it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  85%|████████▍ | 11/13 [00:00<00:00, 78.13it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  92%|█████████▏| 12/13 [00:00<00:00, 78.69it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25:  92%|█████████▏| 12/13 [00:00<00:00, 78.57it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 79.38it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 79.28it/s, v_num=ld_4, val_loss=0.609, train_loss=0.533]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 72.43it/s, v_num=ld_4, val_loss=0.662, train_loss=0.533]
    Epoch 25: 100%|██████████| 13/13 [00:00<00:00, 72.18it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 25:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]         
    Epoch 26:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:   8%|▊         | 1/13 [00:00<00:00, 79.95it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:   8%|▊         | 1/13 [00:00<00:00, 78.62it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  15%|█▌        | 2/13 [00:00<00:00, 82.58it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  15%|█▌        | 2/13 [00:00<00:00, 81.89it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  23%|██▎       | 3/13 [00:00<00:00, 83.20it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  23%|██▎       | 3/13 [00:00<00:00, 82.73it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  31%|███       | 4/13 [00:00<00:00, 83.39it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  31%|███       | 4/13 [00:00<00:00, 83.04it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  38%|███▊      | 5/13 [00:00<00:00, 84.13it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  38%|███▊      | 5/13 [00:00<00:00, 83.84it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  46%|████▌     | 6/13 [00:00<00:00, 84.42it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  46%|████▌     | 6/13 [00:00<00:00, 84.18it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  54%|█████▍    | 7/13 [00:00<00:00, 84.09it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  54%|█████▍    | 7/13 [00:00<00:00, 83.86it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  62%|██████▏   | 8/13 [00:00<00:00, 84.33it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  62%|██████▏   | 8/13 [00:00<00:00, 84.13it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  69%|██████▉   | 9/13 [00:00<00:00, 84.42it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  69%|██████▉   | 9/13 [00:00<00:00, 84.24it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  77%|███████▋  | 10/13 [00:00<00:00, 84.56it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  77%|███████▋  | 10/13 [00:00<00:00, 84.41it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  85%|████████▍ | 11/13 [00:00<00:00, 84.75it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  85%|████████▍ | 11/13 [00:00<00:00, 84.60it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  92%|█████████▏| 12/13 [00:00<00:00, 84.74it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26:  92%|█████████▏| 12/13 [00:00<00:00, 84.62it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26: 100%|██████████| 13/13 [00:00<00:00, 84.72it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26: 100%|██████████| 13/13 [00:00<00:00, 84.61it/s, v_num=ld_4, val_loss=0.662, train_loss=0.554]
    Epoch 26: 100%|██████████| 13/13 [00:00<00:00, 76.99it/s, v_num=ld_4, val_loss=0.638, train_loss=0.554]
    Epoch 26: 100%|██████████| 13/13 [00:00<00:00, 76.72it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 26:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]         
    Epoch 27:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:   8%|▊         | 1/13 [00:00<00:00, 85.62it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:   8%|▊         | 1/13 [00:00<00:00, 84.01it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  15%|█▌        | 2/13 [00:00<00:00, 86.44it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  15%|█▌        | 2/13 [00:00<00:00, 85.68it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  23%|██▎       | 3/13 [00:00<00:00, 86.64it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  23%|██▎       | 3/13 [00:00<00:00, 86.08it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  31%|███       | 4/13 [00:00<00:00, 87.17it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  31%|███       | 4/13 [00:00<00:00, 86.78it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  38%|███▊      | 5/13 [00:00<00:00, 86.81it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  38%|███▊      | 5/13 [00:00<00:00, 86.47it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  46%|████▌     | 6/13 [00:00<00:00, 86.80it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  46%|████▌     | 6/13 [00:00<00:00, 86.54it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  54%|█████▍    | 7/13 [00:00<00:00, 86.57it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  54%|█████▍    | 7/13 [00:00<00:00, 86.34it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  62%|██████▏   | 8/13 [00:00<00:00, 86.71it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  62%|██████▏   | 8/13 [00:00<00:00, 86.52it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  69%|██████▉   | 9/13 [00:00<00:00, 86.83it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  69%|██████▉   | 9/13 [00:00<00:00, 86.64it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  77%|███████▋  | 10/13 [00:00<00:00, 86.85it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  77%|███████▋  | 10/13 [00:00<00:00, 86.69it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  85%|████████▍ | 11/13 [00:00<00:00, 86.55it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  85%|████████▍ | 11/13 [00:00<00:00, 86.39it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  92%|█████████▏| 12/13 [00:00<00:00, 86.52it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27:  92%|█████████▏| 12/13 [00:00<00:00, 86.37it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27: 100%|██████████| 13/13 [00:00<00:00, 86.89it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27: 100%|██████████| 13/13 [00:00<00:00, 86.76it/s, v_num=ld_4, val_loss=0.638, train_loss=0.551]
    Epoch 27: 100%|██████████| 13/13 [00:00<00:00, 78.84it/s, v_num=ld_4, val_loss=0.635, train_loss=0.551]
    Epoch 27: 100%|██████████| 13/13 [00:00<00:00, 78.56it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 27:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]         
    Epoch 28:   0%|          | 0/13 [00:00<?, ?it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:   8%|▊         | 1/13 [00:00<00:00, 88.05it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:   8%|▊         | 1/13 [00:00<00:00, 86.50it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  15%|█▌        | 2/13 [00:00<00:00, 85.76it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  15%|█▌        | 2/13 [00:00<00:00, 85.01it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  23%|██▎       | 3/13 [00:00<00:00, 85.39it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  23%|██▎       | 3/13 [00:00<00:00, 84.84it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  31%|███       | 4/13 [00:00<00:00, 85.58it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  31%|███       | 4/13 [00:00<00:00, 85.21it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  38%|███▊      | 5/13 [00:00<00:00, 85.34it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  38%|███▊      | 5/13 [00:00<00:00, 85.02it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  46%|████▌     | 6/13 [00:00<00:00, 85.60it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  46%|████▌     | 6/13 [00:00<00:00, 85.35it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  54%|█████▍    | 7/13 [00:00<00:00, 85.82it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  54%|█████▍    | 7/13 [00:00<00:00, 85.58it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  62%|██████▏   | 8/13 [00:00<00:00, 85.96it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  62%|██████▏   | 8/13 [00:00<00:00, 85.77it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  69%|██████▉   | 9/13 [00:00<00:00, 85.69it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  69%|██████▉   | 9/13 [00:00<00:00, 85.51it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  77%|███████▋  | 10/13 [00:00<00:00, 85.19it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  77%|███████▋  | 10/13 [00:00<00:00, 85.04it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  85%|████████▍ | 11/13 [00:00<00:00, 85.43it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  85%|████████▍ | 11/13 [00:00<00:00, 85.30it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  92%|█████████▏| 12/13 [00:00<00:00, 85.45it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28:  92%|█████████▏| 12/13 [00:00<00:00, 85.31it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28: 100%|██████████| 13/13 [00:00<00:00, 85.73it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28: 100%|██████████| 13/13 [00:00<00:00, 85.60it/s, v_num=ld_4, val_loss=0.635, train_loss=0.584]
    Epoch 28: 100%|██████████| 13/13 [00:00<00:00, 77.83it/s, v_num=ld_4, val_loss=0.622, train_loss=0.584]
    Epoch 28: 100%|██████████| 13/13 [00:00<00:00, 77.56it/s, v_num=ld_4, val_loss=0.622, train_loss=0.567]
    Epoch 28: 100%|██████████| 13/13 [00:00<00:00, 77.26it/s, v_num=ld_4, val_loss=0.622, train_loss=0.567]
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
         Validate metric           DataLoader 0
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
            AUROC_val           0.7366946935653687
          Accuracy_val          0.7300000190734863
            val_loss            0.6217707991600037
    ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────




.. GENERATED FROM PYTHON SOURCE LINES 144-149

6. Plotting the results 📊
----------------------------
Now we're ready to plot the results of our model.
We're using the :class:`~.ConfusionMatrix` class to plot the confusion matrix.
We're seeing each fold's confusion matrices separately on the right, and the confusion matrix created from the concatenated validation sets from each fold on the left.

.. GENERATED FROM PYTHON SOURCE LINES 149-154

.. code-block:: Python


    confusion_matrix_fig = ConfusionMatrix.from_final_val_data(
        single_model_list
    )
    plt.show()



.. image-sg:: /auto_examples/training_and_testing/images/sphx_glr_plot_one_model_binary_kfold_006.png
   :alt: TabularCrossmodalMultiheadAttention: confusion matrix, Tabular Crossmodal multi-head attention: auroc=0.605, Fold 1: auroc=0.500, Fold 2: auroc=0.500, Fold 3: auroc=0.812, Fold 4: auroc=0.934, Fold 5: auroc=0.737
   :srcset: /auto_examples/training_and_testing/images/sphx_glr_plot_one_model_binary_kfold_006.png
   :class: sphx-glr-single-img






.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 25.156 seconds)


.. _sphx_glr_download_auto_examples_training_and_testing_plot_one_model_binary_kfold.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_one_model_binary_kfold.ipynb <plot_one_model_binary_kfold.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_one_model_binary_kfold.py <plot_one_model_binary_kfold.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_one_model_binary_kfold.zip <plot_one_model_binary_kfold.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_