Note

Go to the end to download the full example code

Train/Test split: Regression๏ƒ

๐Ÿš€ In this tutorial, weโ€™ll explore regression using a train/test split. Specifically, weโ€™re using the 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 halfโ€™s values have been inverted to make the task more difficult. The prediction labels (the number shown in the image) has been changed into a continuous variable (1.0, 2.0, 3.0, etc.) and had some noise added to it. So the labels look more like 1.05, 2.02, 3.01, etc.

Key Features:

  • ๐Ÿ“ฅ Importing a model based on its path.

  • ๐Ÿงช Training and testing a model with train/test split.

  • ๐Ÿ“ˆ Plotting the loss curves of each fold.

  • ๐Ÿ“Š Visualising the results of a single train/test model using the RealsVsPreds class.

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

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

# sphinx_gallery_thumbnail_number = -1

1. Import the fusion model ๐Ÿ”๏ƒ

Weโ€™re importing only one model for this example, the TabularCrossmodalMultiheadAttention model. Instead of using the import_chosen_fusion_models() function, weโ€™re importing the model directly like with any other library method.

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

2. Set the training parameters ๐ŸŽฏ๏ƒ

Now weโ€™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 canโ€™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.

# Regression task
prediction_task = "regression"

# Set the batch size
batch_size = 32

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

# 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))

3. Specifying input file paths ๐Ÿ”ฎ๏ƒ

Weโ€™re using the MNIST dataset for this example, and the CSV files are stored in the _static/mnist_data directory with the documentation files.

data_paths = {
    "tabular1": "../../_static/mnist_data/mnist1_regression.csv",
    "tabular2": "../../_static/mnist_data/mnist2_regression.csv",
    "image": "",
}

4. Training the fusion model ๐Ÿ๏ƒ

Now weโ€™re ready to train our model. Weโ€™re using the train_and_save_models() function to train our model.

First we need to create a data module using the 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 train_and_save_models() function. Weโ€™re not using checkpointing for this example, so we set enable_checkpointing=False. Weโ€™re also setting show_loss_plot=True to plot the loss curve.

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,
                         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,
    metrics_list=["r2", "mae", "mse"]
)
Loss Curves for TabularCrossmodalMultiheadAttention
method_name: Tabular Crossmodal multi-head attention
modality_type: tabular_tabular
fusion_type: attention

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%|โ–Š         | 1/13 [00:00<00:00, 50.63it/s]
Epoch 0:   8%|โ–Š         | 1/13 [00:00<00:00, 49.74it/s, v_num=tion]
Epoch 0:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 55.02it/s, v_num=tion]
Epoch 0:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 54.47it/s, v_num=tion]
Epoch 0:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 57.64it/s, v_num=tion]
Epoch 0:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 57.26it/s, v_num=tion]
Epoch 0:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 59.37it/s, v_num=tion]
Epoch 0:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 59.07it/s, v_num=tion]
Epoch 0:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 60.28it/s, v_num=tion]
Epoch 0:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 60.03it/s, v_num=tion]
Epoch 0:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 60.33it/s, v_num=tion]
Epoch 0:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 60.12it/s, v_num=tion]
Epoch 0:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 61.07it/s, v_num=tion]
Epoch 0:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 60.89it/s, v_num=tion]
Epoch 0:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 61.38it/s, v_num=tion]
Epoch 0:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 61.23it/s, v_num=tion]
Epoch 0:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 61.71it/s, v_num=tion]
Epoch 0:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 61.56it/s, v_num=tion]
Epoch 0:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 61.69it/s, v_num=tion]
Epoch 0:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 61.56it/s, v_num=tion]
Epoch 0:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 61.69it/s, v_num=tion]
Epoch 0:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 61.57it/s, v_num=tion]
Epoch 0:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 61.90it/s, v_num=tion]
Epoch 0:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 61.79it/s, v_num=tion]
Epoch 0: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.23it/s, v_num=tion]
Epoch 0: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.13it/s, v_num=tion]
Epoch 0: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 56.18it/s, v_num=tion, val_loss=6.790]
Epoch 0: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 55.95it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 0:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:   8%|โ–Š         | 1/13 [00:00<00:00, 64.61it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:   8%|โ–Š         | 1/13 [00:00<00:00, 63.19it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 63.83it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 63.10it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 63.95it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 63.44it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 64.48it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 64.10it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 64.61it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 64.31it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 64.54it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 64.27it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 64.07it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 63.85it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 64.26it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 64.07it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 64.30it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 64.12it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 64.28it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 64.13it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 64.02it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 63.88it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 64.14it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 64.01it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 64.42it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 64.30it/s, v_num=tion, val_loss=6.790, train_loss=13.30]
Epoch 1: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 58.85it/s, v_num=tion, val_loss=6.450, train_loss=13.30]
Epoch 1: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 58.60it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 1:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:   8%|โ–Š         | 1/13 [00:00<00:00, 61.25it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:   8%|โ–Š         | 1/13 [00:00<00:00, 59.85it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 62.35it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 61.60it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 62.83it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 62.33it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 63.47it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 63.09it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 63.90it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 63.59it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 62.89it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 62.63it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 63.26it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 63.04it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 63.49it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 63.30it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 63.63it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 63.46it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 63.40it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 63.25it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 63.46it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 63.32it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 63.51it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 63.39it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.85it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.73it/s, v_num=tion, val_loss=6.450, train_loss=5.370]
Epoch 2: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 58.19it/s, v_num=tion, val_loss=3.780, train_loss=5.370]
Epoch 2: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 57.93it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 2:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:   8%|โ–Š         | 1/13 [00:00<00:00, 65.04it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:   8%|โ–Š         | 1/13 [00:00<00:00, 63.60it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 64.80it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 64.00it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 64.50it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 64.00it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 63.93it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 63.55it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 64.28it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 63.95it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 64.34it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 64.07it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 64.44it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 64.22it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 63.87it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 63.66it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 63.98it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 63.76it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 64.05it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 63.90it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 64.04it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 63.90it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 63.83it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 63.70it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 64.11it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 64.00it/s, v_num=tion, val_loss=3.780, train_loss=3.940]
Epoch 3: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 58.60it/s, v_num=tion, val_loss=4.510, train_loss=3.940]
Epoch 3: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 58.34it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 3:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:   8%|โ–Š         | 1/13 [00:00<00:00, 64.63it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:   8%|โ–Š         | 1/13 [00:00<00:00, 63.19it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 63.26it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 62.53it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 63.96it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 63.47it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 64.56it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 64.19it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 65.16it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 64.87it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 65.66it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 65.42it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 65.56it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 65.35it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 65.81it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 65.62it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 66.10it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 65.94it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 66.46it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 66.32it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 66.47it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 66.34it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 66.74it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 66.62it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 67.20it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 67.09it/s, v_num=tion, val_loss=4.510, train_loss=2.770]
Epoch 4: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 61.44it/s, v_num=tion, val_loss=3.360, train_loss=2.770]
Epoch 4: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 61.19it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 4:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:   8%|โ–Š         | 1/13 [00:00<00:00, 65.39it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:   8%|โ–Š         | 1/13 [00:00<00:00, 64.16it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.43it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 66.76it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 67.26it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 66.80it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.06it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 66.69it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 66.53it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 66.25it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 66.34it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 66.10it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 66.51it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 66.31it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 66.85it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 66.66it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 67.07it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 66.91it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 66.84it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 66.70it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 67.04it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 66.90it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 67.25it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 67.13it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 67.67it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 67.55it/s, v_num=tion, val_loss=3.360, train_loss=2.520]
Epoch 5: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 61.54it/s, v_num=tion, val_loss=2.900, train_loss=2.520]
Epoch 5: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 61.29it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 5:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:   8%|โ–Š         | 1/13 [00:00<00:00, 68.26it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:   8%|โ–Š         | 1/13 [00:00<00:00, 66.69it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.20it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.47it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 67.80it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 67.31it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.43it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.08it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.00it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 67.72it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.35it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.12it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.70it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.50it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.92it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.75it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.77it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.62it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.70it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.56it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.53it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.40it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.60it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.48it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.60it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.48it/s, v_num=tion, val_loss=2.900, train_loss=1.640]
Epoch 6: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.60it/s, v_num=tion, val_loss=3.230, train_loss=1.640]
Epoch 6: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.34it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 6:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:   8%|โ–Š         | 1/13 [00:00<00:00, 69.51it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:   8%|โ–Š         | 1/13 [00:00<00:00, 68.15it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 69.61it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.76it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.15it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.63it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.93it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.56it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.30it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.02it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.61it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.34it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 67.78it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 67.54it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 66.80it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 66.60it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 66.74it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 66.55it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 66.39it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 66.23it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 66.35it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 66.21it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 66.05it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 65.93it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 66.24it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 66.14it/s, v_num=tion, val_loss=3.230, train_loss=1.160]
Epoch 7: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 60.54it/s, v_num=tion, val_loss=2.510, train_loss=1.160]
Epoch 7: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 60.30it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 7:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:   8%|โ–Š         | 1/13 [00:00<00:00, 69.45it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:   8%|โ–Š         | 1/13 [00:00<00:00, 68.03it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.04it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.37it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.06it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.60it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.14it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.79it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.29it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.98it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.53it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.29it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.22it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.02it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.42it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.23it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.33it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.16it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.36it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.19it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.00it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.87it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.13it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.01it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.47it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.37it/s, v_num=tion, val_loss=2.510, train_loss=0.981]
Epoch 8: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.76it/s, v_num=tion, val_loss=2.980, train_loss=0.981]
Epoch 8: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.48it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 8:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:   8%|โ–Š         | 1/13 [00:00<00:00, 62.47it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:   8%|โ–Š         | 1/13 [00:00<00:00, 61.32it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 65.53it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 64.85it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 66.50it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 66.05it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 66.65it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 66.31it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 66.72it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 66.44it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 66.77it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 66.54it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 67.29it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 67.10it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.79it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.63it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.21it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.06it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 67.90it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 67.76it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.02it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 67.85it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 67.95it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 67.84it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.18it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.06it/s, v_num=tion, val_loss=2.980, train_loss=0.664]
Epoch 9: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 61.93it/s, v_num=tion, val_loss=3.030, train_loss=0.664]
Epoch 9: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 61.66it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 9:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:   8%|โ–Š         | 1/13 [00:00<00:00, 69.17it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:   8%|โ–Š         | 1/13 [00:00<00:00, 67.69it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 69.28it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.61it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.85it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.39it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.56it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.21it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 66.32it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 66.06it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 66.23it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 65.99it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 66.53it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 66.35it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.08it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 66.92it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 67.09it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 66.92it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 67.11it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 66.96it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 67.06it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 66.92it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 67.23it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 67.09it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 67.19it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 67.07it/s, v_num=tion, val_loss=3.030, train_loss=0.514]
Epoch 10: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 61.33it/s, v_num=tion, val_loss=2.780, train_loss=0.514]
Epoch 10: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 61.07it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 10:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:   8%|โ–Š         | 1/13 [00:00<00:00, 68.47it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:   8%|โ–Š         | 1/13 [00:00<00:00, 67.13it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.82it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.12it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.25it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.77it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.47it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.11it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.60it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.30it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.67it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.41it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.49it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.26it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.02it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.83it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.11it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 67.94it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.25it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.10it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.38it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.24it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.27it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.15it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.63it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.52it/s, v_num=tion, val_loss=2.780, train_loss=0.457]
Epoch 11: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.68it/s, v_num=tion, val_loss=2.860, train_loss=0.457]
Epoch 11: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.42it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 11:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:   8%|โ–Š         | 1/13 [00:00<00:00, 69.83it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:   8%|โ–Š         | 1/13 [00:00<00:00, 68.44it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.69it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.96it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.36it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.90it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.92it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.56it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 70.26it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.96it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 70.50it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 70.26it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 70.14it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.94it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 70.15it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.96it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 70.07it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.90it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 70.02it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.86it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.71it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.58it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.51it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.38it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.70it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.58it/s, v_num=tion, val_loss=2.860, train_loss=0.370]
Epoch 12: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.43it/s, v_num=tion, val_loss=2.900, train_loss=0.370]
Epoch 12: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.16it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 12:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:   8%|โ–Š         | 1/13 [00:00<00:00, 64.13it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:   8%|โ–Š         | 1/13 [00:00<00:00, 62.84it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 66.77it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 66.10it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 67.53it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 67.09it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.39it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.05it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.83it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.55it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 67.57it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 67.29it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 67.34it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 67.09it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.43it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.23it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 67.30it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 67.12it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 66.52it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 66.35it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 66.25it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 66.11it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 66.37it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 66.25it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 66.67it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 66.55it/s, v_num=tion, val_loss=2.900, train_loss=0.340]
Epoch 13: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 60.64it/s, v_num=tion, val_loss=2.320, train_loss=0.340]
Epoch 13: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 60.39it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 13:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:   8%|โ–Š         | 1/13 [00:00<00:00, 67.93it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:   8%|โ–Š         | 1/13 [00:00<00:00, 66.58it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.85it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.16it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.27it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.75it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.76it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.40it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.07it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.79it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.37it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.14it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.61it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.41it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.85it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.68it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.60it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.43it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.31it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.15it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.14it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.00it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.04it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.93it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.11it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.00it/s, v_num=tion, val_loss=2.320, train_loss=0.338]
Epoch 14: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.08it/s, v_num=tion, val_loss=2.430, train_loss=0.338]
Epoch 14: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.82it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 14:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:   8%|โ–Š         | 1/13 [00:00<00:00, 69.10it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:   8%|โ–Š         | 1/13 [00:00<00:00, 67.69it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 69.23it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.51it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.89it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.40it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.19it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.83it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.63it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.35it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.00it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.75it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.26it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.06it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.84it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.65it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.90it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.74it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.85it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.70it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.95it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.82it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.78it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.66it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.09it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.97it/s, v_num=tion, val_loss=2.430, train_loss=0.280]
Epoch 15: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.95it/s, v_num=tion, val_loss=2.490, train_loss=0.280]
Epoch 15: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.66it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 15:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:   8%|โ–Š         | 1/13 [00:00<00:00, 68.21it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:   8%|โ–Š         | 1/13 [00:00<00:00, 66.73it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 66.49it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 65.83it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 65.68it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 65.25it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 66.28it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 65.93it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 66.86it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 66.57it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 67.23it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 66.99it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 67.01it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 66.81it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.29it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.11it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 67.10it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 66.90it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 67.03it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 66.87it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 66.44it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 66.30it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 66.59it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 66.47it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 66.98it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 66.89it/s, v_num=tion, val_loss=2.490, train_loss=0.213]
Epoch 16: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 60.98it/s, v_num=tion, val_loss=2.370, train_loss=0.213]
Epoch 16: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 60.72it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 16:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:   8%|โ–Š         | 1/13 [00:00<00:00, 62.29it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:   8%|โ–Š         | 1/13 [00:00<00:00, 61.10it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 65.16it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 64.52it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 66.68it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 66.23it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.48it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.11it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 67.01it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 66.73it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 66.54it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 66.32it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 67.04it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 66.85it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.49it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.32it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 67.89it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 67.74it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 67.92it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 67.77it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.16it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.03it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.39it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.27it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.84it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.73it/s, v_num=tion, val_loss=2.370, train_loss=0.170]
Epoch 17: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.60it/s, v_num=tion, val_loss=2.330, train_loss=0.170]
Epoch 17: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.33it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 17:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:   8%|โ–Š         | 1/13 [00:00<00:00, 67.64it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:   8%|โ–Š         | 1/13 [00:00<00:00, 66.27it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.46it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.74it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.91it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.45it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.46it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.11it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.95it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.67it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.09it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.86it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.41it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.21it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.43it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.25it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.08it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.92it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.17it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.02it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.95it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.81it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.63it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.50it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.52it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.40it/s, v_num=tion, val_loss=2.330, train_loss=0.109]
Epoch 18: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.47it/s, v_num=tion, val_loss=2.420, train_loss=0.109]
Epoch 18: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.20it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 18:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:   8%|โ–Š         | 1/13 [00:00<00:00, 68.48it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:   8%|โ–Š         | 1/13 [00:00<00:00, 67.15it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 69.19it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.51it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.79it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.30it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.70it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.36it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.87it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.60it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.89it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.67it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.93it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.71it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.53it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.36it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.83it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.67it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.94it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.80it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.16it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.03it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.05it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.94it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.43it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.31it/s, v_num=tion, val_loss=2.420, train_loss=0.103]
Epoch 19: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.34it/s, v_num=tion, val_loss=2.270, train_loss=0.103]
Epoch 19: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.08it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 19:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:   8%|โ–Š         | 1/13 [00:00<00:00, 69.81it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:   8%|โ–Š         | 1/13 [00:00<00:00, 68.43it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.74it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.06it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.51it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.03it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.81it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.45it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 70.09it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.79it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 70.04it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.80it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.39it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.17it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.50it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.32it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.65it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.49it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.74it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.59it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.36it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.23it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.45it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.34it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.75it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.63it/s, v_num=tion, val_loss=2.270, train_loss=0.0828]
Epoch 20: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.56it/s, v_num=tion, val_loss=2.230, train_loss=0.0828]
Epoch 20: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.29it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 20:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:   8%|โ–Š         | 1/13 [00:00<00:00, 66.36it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:   8%|โ–Š         | 1/13 [00:00<00:00, 65.12it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.60it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.88it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.64it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.18it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.92it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.53it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 70.10it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.81it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.53it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.28it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.68it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.48it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.82it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.64it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 70.05it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.89it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.87it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.72it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.89it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.73it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.96it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.84it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 70.26it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 70.15it/s, v_num=tion, val_loss=2.230, train_loss=0.0655]
Epoch 21: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.83it/s, v_num=tion, val_loss=2.240, train_loss=0.0655]
Epoch 21: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.56it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 21:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:   8%|โ–Š         | 1/13 [00:00<00:00, 70.00it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:   8%|โ–Š         | 1/13 [00:00<00:00, 68.60it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 70.24it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 69.54it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 70.38it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.90it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.86it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.51it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 70.03it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.71it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 70.13it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.89it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.86it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.66it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.71it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.54it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.64it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.48it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.81it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.66it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.84it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.72it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.71it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.59it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 70.08it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.97it/s, v_num=tion, val_loss=2.240, train_loss=0.0614]
Epoch 22: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.96it/s, v_num=tion, val_loss=2.180, train_loss=0.0614]
Epoch 22: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.68it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 22:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:   8%|โ–Š         | 1/13 [00:00<00:00, 70.31it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:   8%|โ–Š         | 1/13 [00:00<00:00, 68.72it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 69.01it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.32it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.49it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.99it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.53it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.16it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.64it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.35it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.77it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.53it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.41it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.21it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.51it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.33it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.52it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.36it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.59it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.44it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.33it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.20it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.44it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.32it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.75it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.65it/s, v_num=tion, val_loss=2.180, train_loss=0.0692]
Epoch 23: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.61it/s, v_num=tion, val_loss=2.230, train_loss=0.0692]
Epoch 23: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.35it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 23:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:   8%|โ–Š         | 1/13 [00:00<00:00, 67.55it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:   8%|โ–Š         | 1/13 [00:00<00:00, 66.27it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 69.46it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.77it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 70.06it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.58it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 70.22it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.74it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.94it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.64it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.99it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.77it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.20it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.01it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.51it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.34it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.72it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.57it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.61it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.46it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.81it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.69it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.98it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.86it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 70.30it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 70.19it/s, v_num=tion, val_loss=2.230, train_loss=0.0511]
Epoch 24: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.93it/s, v_num=tion, val_loss=2.310, train_loss=0.0511]
Epoch 24: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.65it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 24:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:   8%|โ–Š         | 1/13 [00:00<00:00, 69.20it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:   8%|โ–Š         | 1/13 [00:00<00:00, 67.79it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 69.74it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 69.04it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 70.02it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.54it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.97it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.60it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.45it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.18it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.84it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.59it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 70.06it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.84it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.78it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.61it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 70.02it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.86it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 70.17it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 70.02it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 70.21it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 70.01it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.72it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.54it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.66it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.55it/s, v_num=tion, val_loss=2.310, train_loss=0.0384]
Epoch 25: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.50it/s, v_num=tion, val_loss=2.380, train_loss=0.0384]
Epoch 25: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.24it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 25:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:   8%|โ–Š         | 1/13 [00:00<00:00, 69.39it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:   8%|โ–Š         | 1/13 [00:00<00:00, 68.01it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.40it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 66.69it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.18it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 67.72it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.80it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.44it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.09it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.81it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.40it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.16it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.12it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.92it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.33it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.13it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.89it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.71it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.83it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.68it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.65it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.52it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.81it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.69it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.18it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.07it/s, v_num=tion, val_loss=2.380, train_loss=0.051]
Epoch 26: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.03it/s, v_num=tion, val_loss=2.060, train_loss=0.051]
Epoch 26: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.75it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 26:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:   8%|โ–Š         | 1/13 [00:00<00:00, 63.13it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:   8%|โ–Š         | 1/13 [00:00<00:00, 62.00it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 66.46it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 65.84it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 67.92it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 67.47it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.53it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.19it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.05it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.78it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.94it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.69it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.26it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.07it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.54it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.35it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.79it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.64it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.58it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.44it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.75it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.62it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.84it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.72it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 70.15it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 70.04it/s, v_num=tion, val_loss=2.060, train_loss=0.0466]
Epoch 27: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.64it/s, v_num=tion, val_loss=2.120, train_loss=0.0466]
Epoch 27: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.38it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 27:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:   8%|โ–Š         | 1/13 [00:00<00:00, 70.33it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:   8%|โ–Š         | 1/13 [00:00<00:00, 68.93it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 69.83it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 69.06it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.19it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.72it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.90it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.55it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.33it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.04it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.51it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.27it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.26it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.06it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.91it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.73it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.07it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.90it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.15it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.99it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.26it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.13it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.08it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.96it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.46it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.36it/s, v_num=tion, val_loss=2.120, train_loss=0.0383]
Epoch 28: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.13it/s, v_num=tion, val_loss=2.130, train_loss=0.0383]
Epoch 28: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.88it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 28:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:   8%|โ–Š         | 1/13 [00:00<00:00, 69.10it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:   8%|โ–Š         | 1/13 [00:00<00:00, 67.62it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 65.92it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 65.23it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 66.42it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 65.97it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 65.92it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 65.57it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 66.54it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 66.25it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 67.09it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 66.86it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 67.12it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 66.93it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.56it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.39it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 67.98it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 67.82it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.28it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.14it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.23it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.11it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.47it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.35it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.86it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.74it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.90it/s, v_num=tion, val_loss=2.130, train_loss=0.0212]
Epoch 29: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.64it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 29:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:   8%|โ–Š         | 1/13 [00:00<00:00, 67.18it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:   8%|โ–Š         | 1/13 [00:00<00:00, 65.88it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.68it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 66.88it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.25it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 67.75it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.82it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.45it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 67.80it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 67.47it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 67.13it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 66.88it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 67.08it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 66.84it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 66.22it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 66.00it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 66.01it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 65.83it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 65.85it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 65.70it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 66.17it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 66.05it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 66.52it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 66.40it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 67.00it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 66.90it/s, v_num=tion, val_loss=2.130, train_loss=0.0184]
Epoch 30: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 60.99it/s, v_num=tion, val_loss=2.110, train_loss=0.0184]
Epoch 30: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 60.74it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 30:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:   8%|โ–Š         | 1/13 [00:00<00:00, 67.66it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:   8%|โ–Š         | 1/13 [00:00<00:00, 66.32it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.51it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.83it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.28it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.82it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.03it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.69it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.42it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.14it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.57it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.33it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.63it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.41it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.08it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.90it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.31it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.15it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.56it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.42it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.76it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.63it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.62it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.50it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.97it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.86it/s, v_num=tion, val_loss=2.110, train_loss=0.0204]
Epoch 31: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.82it/s, v_num=tion, val_loss=2.190, train_loss=0.0204]
Epoch 31: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.55it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 31:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:   8%|โ–Š         | 1/13 [00:00<00:00, 70.99it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:   8%|โ–Š         | 1/13 [00:00<00:00, 69.49it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.72it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.04it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.29it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.83it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.71it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.24it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.90it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.62it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.97it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.71it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.54it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.33it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.75it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.57it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.01it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.85it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.11it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.95it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.73it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.59it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.93it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.81it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.15it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.03it/s, v_num=tion, val_loss=2.190, train_loss=0.0326]
Epoch 32: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.90it/s, v_num=tion, val_loss=2.140, train_loss=0.0326]
Epoch 32: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.62it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 32:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:   8%|โ–Š         | 1/13 [00:00<00:00, 66.75it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:   8%|โ–Š         | 1/13 [00:00<00:00, 65.49it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.59it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.91it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.45it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.98it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.47it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.11it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.78it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.50it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.38it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.14it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.65it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.45it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.71it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.50it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.56it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.39it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.22it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.07it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.22it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.08it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.24it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.11it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.33it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.21it/s, v_num=tion, val_loss=2.140, train_loss=0.0282]
Epoch 33: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.74it/s, v_num=tion, val_loss=2.160, train_loss=0.0282]
Epoch 33: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.48it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 33:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:   8%|โ–Š         | 1/13 [00:00<00:00, 65.31it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:   8%|โ–Š         | 1/13 [00:00<00:00, 64.06it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 66.99it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 66.33it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 67.87it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 67.41it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.37it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.03it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.09it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 67.82it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.57it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.34it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.84it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.64it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.22it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.04it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.12it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.97it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.39it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.25it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.57it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.44it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.67it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.54it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.34it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.22it/s, v_num=tion, val_loss=2.160, train_loss=0.026]
Epoch 34: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.20it/s, v_num=tion, val_loss=2.150, train_loss=0.026]
Epoch 34: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.93it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 34:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:   8%|โ–Š         | 1/13 [00:00<00:00, 69.05it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:   8%|โ–Š         | 1/13 [00:00<00:00, 67.68it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 69.59it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.89it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 70.09it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.62it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.03it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.69it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.38it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.09it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.06it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.82it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.27it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.05it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.94it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.75it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.16it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 67.99it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.35it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.21it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.37it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.22it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.14it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.02it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.50it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.39it/s, v_num=tion, val_loss=2.150, train_loss=0.0174]
Epoch 35: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.56it/s, v_num=tion, val_loss=2.170, train_loss=0.0174]
Epoch 35: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.30it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 35:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:   8%|โ–Š         | 1/13 [00:00<00:00, 69.71it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:   8%|โ–Š         | 1/13 [00:00<00:00, 68.31it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.06it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.37it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 67.44it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 66.97it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.81it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.46it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.44it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.17it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.87it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.62it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.59it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.39it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.16it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 67.94it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 67.52it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 67.34it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 67.46it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 67.30it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 66.68it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 66.52it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 66.63it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 66.51it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 67.02it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 66.91it/s, v_num=tion, val_loss=2.170, train_loss=0.0178]
Epoch 36: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 61.29it/s, v_num=tion, val_loss=2.120, train_loss=0.0178]
Epoch 36: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 61.04it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 36:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:   8%|โ–Š         | 1/13 [00:00<00:00, 65.67it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:   8%|โ–Š         | 1/13 [00:00<00:00, 64.43it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.10it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.38it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 69.04it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.59it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.64it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 69.29it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 70.09it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.81it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.84it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.60it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 70.09it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.86it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 70.16it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.98it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 70.32it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 70.16it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.91it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 69.76it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.87it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 69.71it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.96it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.84it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 70.27it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 70.15it/s, v_num=tion, val_loss=2.120, train_loss=0.0187]
Epoch 37: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.77it/s, v_num=tion, val_loss=2.060, train_loss=0.0187]
Epoch 37: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.50it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 37:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:   8%|โ–Š         | 1/13 [00:00<00:00, 65.52it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:   8%|โ–Š         | 1/13 [00:00<00:00, 64.13it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.79it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.14it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.78it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.32it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.72it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 68.38it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 69.26it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.98it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.61it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 69.37it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.63it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 69.44it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.58it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 69.39it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.13it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.97it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.84it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.68it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.58it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.44it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.57it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.44it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.23it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 68.11it/s, v_num=tion, val_loss=2.060, train_loss=0.0173]
Epoch 38: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.29it/s, v_num=tion, val_loss=2.110, train_loss=0.0173]
Epoch 38: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.04it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 38:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:   8%|โ–Š         | 1/13 [00:00<00:00, 69.65it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:   8%|โ–Š         | 1/13 [00:00<00:00, 68.28it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 68.66it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 67.87it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.70it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 68.20it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.51it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.08it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 66.39it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 66.03it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 65.65it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 65.36it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 65.20it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 64.97it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 64.73it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 64.54it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 64.98it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 64.81it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 64.76it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 64.60it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 64.88it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 64.74it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 64.64it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 64.50it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 64.60it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 64.48it/s, v_num=tion, val_loss=2.110, train_loss=0.0182]
Epoch 39: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 58.84it/s, v_num=tion, val_loss=2.070, train_loss=0.0182]
Epoch 39: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 58.58it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 39:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:   8%|โ–Š         | 1/13 [00:00<00:00, 64.89it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:   8%|โ–Š         | 1/13 [00:00<00:00, 63.55it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 63.56it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 62.86it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 64.51it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 64.02it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 65.14it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 64.74it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 65.51it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 65.21it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 65.83it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 65.57it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 65.35it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 65.13it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 65.46it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 65.27it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 65.61it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 65.43it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 65.57it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 65.42it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 65.43it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 65.30it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 65.59it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 65.46it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 65.67it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 65.54it/s, v_num=tion, val_loss=2.070, train_loss=0.0189]
Epoch 40: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 59.83it/s, v_num=tion, val_loss=2.080, train_loss=0.0189]
Epoch 40: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 59.56it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 40:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:   0%|          | 0/13 [00:00<?, ?it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:   8%|โ–Š         | 1/13 [00:00<00:00, 62.17it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:   8%|โ–Š         | 1/13 [00:00<00:00, 61.03it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 65.55it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  15%|โ–ˆโ–Œ        | 2/13 [00:00<00:00, 64.93it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 67.10it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  23%|โ–ˆโ–ˆโ–Ž       | 3/13 [00:00<00:00, 66.67it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.96it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  31%|โ–ˆโ–ˆโ–ˆ       | 4/13 [00:00<00:00, 67.63it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.52it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  38%|โ–ˆโ–ˆโ–ˆโ–Š      | 5/13 [00:00<00:00, 68.25it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.26it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  46%|โ–ˆโ–ˆโ–ˆโ–ˆโ–Œ     | 6/13 [00:00<00:00, 68.02it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.61it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  54%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–    | 7/13 [00:00<00:00, 68.34it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.91it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  62%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–   | 8/13 [00:00<00:00, 68.74it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 69.02it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  69%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‰   | 9/13 [00:00<00:00, 68.87it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.95it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  77%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‹  | 10/13 [00:00<00:00, 68.82it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.99it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  85%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ– | 11/13 [00:00<00:00, 68.87it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 69.09it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41:  92%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–| 12/13 [00:00<00:00, 68.97it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.44it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 69.32it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 63.03it/s, v_num=tion, val_loss=2.080, train_loss=0.0172]
Epoch 41: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.77it/s, v_num=tion, val_loss=2.080, train_loss=0.0186]
Epoch 41: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 13/13 [00:00<00:00, 62.39it/s, v_num=tion, val_loss=2.080, train_loss=0.0186]
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
     Validate metric           DataLoader 0
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
         mae_val            1.0560115575790405
         mse_val             2.075087070465088
         r2_val             0.7391142249107361
        val_loss             2.075087070465088
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€

6. Plotting the results ๐Ÿ“Š๏ƒ

Now weโ€™re ready to plot the results of our model. Weโ€™re using the RealsVsPreds class to plot the confusion matrix.

reals_preds_fig = RealsVsPreds.from_final_val_data(
    single_model_list
)
plt.show()
Evaluation: Validation Data, Tabular Crossmodal multi-head attention - Validation r2: 0.739

Total running time of the script: (0 minutes 9.548 seconds)

Gallery generated by Sphinx-Gallery