Using External Test Data

Let’s learn how to use external test data with Fusilli! Some guidance can also be found in the Data Loading section of the documentation.

The extra step that we need to take is to provide the paths to the test data files to the functions that create evaluation figures: from_new_data, from_new_data, from_new_data.

Note

It is not possible to use external test data with graph-based fusion models.

We’ll rush through the first few steps of the training and testing process, as they are covered in more detail in the other example notebooks.

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
from fusilli.utils.model_chooser import import_chosen_fusion_models

# sphinx_gallery_thumbnail_number = -1


model_conditions = {
    "class_name": ["ConcatTabularFeatureMaps"],
}

fusion_models = import_chosen_fusion_models(model_conditions)

# Regression task
prediction_task = "regression"

# Set the batch size
batch_size = 48

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

for dir in output_paths.values():
    os.makedirs(dir, 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))

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

external_data_paths = {
    "tabular1": "../../_static/mnist_data/mnist1_regression_test.csv",
    "tabular2": "../../_static/mnist_data/mnist2_regression_test.csv",
    "image": "",
}

fusion_model = fusion_models[0]

print("Method name:", fusion_model.method_name)
print("Modality type:", fusion_model.modality_type)
print("Fusion type:", fusion_model.fusion_type)

# Create the data module
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
trained_model = train_and_save_models(
    data_module=dm,
    fusion_model=fusion_model,
    enable_checkpointing=True,
    show_loss_plot=True,
)
Loss Curves for ConcatTabularFeatureMaps
Imported methods:
['Concatenating tabular feature maps']
Method name: Concatenating tabular feature maps
Modality type: tabular_tabular
Fusion type: operation

Training: |          | 0/? [00:00<?, ?it/s]
Training:   0%|          | 0/9 [00:00<?, ?it/s]
Epoch 0:   0%|          | 0/9 [00:00<?, ?it/s]
Epoch 0:  11%|β–ˆ         | 1/9 [00:00<00:00, 59.02it/s]
Epoch 0:  11%|β–ˆ         | 1/9 [00:00<00:00, 57.83it/s, v_num=Maps]
Epoch 0:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 66.34it/s, v_num=Maps]
Epoch 0:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 65.62it/s, v_num=Maps]
Epoch 0:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 70.42it/s, v_num=Maps]
Epoch 0:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 69.90it/s, v_num=Maps]
Epoch 0:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 73.30it/s, v_num=Maps]
Epoch 0:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 72.89it/s, v_num=Maps]
Epoch 0:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 75.34it/s, v_num=Maps]
Epoch 0:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 74.99it/s, v_num=Maps]
Epoch 0:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 76.45it/s, v_num=Maps]
Epoch 0:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 76.15it/s, v_num=Maps]
Epoch 0:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 76.76it/s, v_num=Maps]
Epoch 0:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 76.50it/s, v_num=Maps]
Epoch 0:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 77.49it/s, v_num=Maps]
Epoch 0:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 77.27it/s, v_num=Maps]
Epoch 0: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 78.95it/s, v_num=Maps]
Epoch 0: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 78.75it/s, v_num=Maps]
Epoch 0: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 70.37it/s, v_num=Maps, val_loss=7.180]
Epoch 0: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 69.89it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 0:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.28it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  11%|β–ˆ         | 1/9 [00:00<00:00, 72.48it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.05it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.11it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.76it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.13it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.39it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.90it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.32it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.90it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.96it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.61it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.49it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.20it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.94it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.62it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.84it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.61it/s, v_num=Maps, val_loss=7.180, train_loss=13.90]
Epoch 1: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.38it/s, v_num=Maps, val_loss=5.340, train_loss=13.90]
Epoch 1: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.83it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 1:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  11%|β–ˆ         | 1/9 [00:00<00:00, 76.16it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.34it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.41it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.98it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.37it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.74it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.83it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.32it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.64it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.19it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.81it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.45it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.48it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.20it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.00it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.74it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.17it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.93it/s, v_num=Maps, val_loss=5.340, train_loss=8.090]
Epoch 2: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.30it/s, v_num=Maps, val_loss=5.450, train_loss=8.090]
Epoch 2: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.74it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 2:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.45it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  11%|β–ˆ         | 1/9 [00:00<00:00, 72.63it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.84it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 76.89it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 79.06it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 78.43it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.39it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 79.91it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.68it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.19it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.67it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.33it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.44it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.16it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.06it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 82.79it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.37it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.14it/s, v_num=Maps, val_loss=5.450, train_loss=5.680]
Epoch 3: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.11it/s, v_num=Maps, val_loss=5.950, train_loss=5.680]
Epoch 3: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 75.57it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 3:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  11%|β–ˆ         | 1/9 [00:00<00:00, 76.68it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.73it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 80.35it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.39it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 82.55it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.84it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.93it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.42it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.80it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.39it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.53it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.12it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.29it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 83.96it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.26it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.99it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.33it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.09it/s, v_num=Maps, val_loss=5.950, train_loss=4.280]
Epoch 4: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.81it/s, v_num=Maps, val_loss=4.330, train_loss=4.280]
Epoch 4: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.25it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 4:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  11%|β–ˆ         | 1/9 [00:00<00:00, 77.21it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.14it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 80.97it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.96it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 82.75it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 82.05it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.28it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.75it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.86it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.45it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.93it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.58it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.52it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.21it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.88it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.62it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.07it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.82it/s, v_num=Maps, val_loss=4.330, train_loss=3.360]
Epoch 5: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.35it/s, v_num=Maps, val_loss=3.960, train_loss=3.360]
Epoch 5: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.76it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 5:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  11%|β–ˆ         | 1/9 [00:00<00:00, 76.14it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.25it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.99it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.04it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 82.12it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.42it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.63it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.13it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.43it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.01it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.39it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.05it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.96it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.63it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.35it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.07it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.28it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.04it/s, v_num=Maps, val_loss=3.960, train_loss=2.880]
Epoch 6: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.66it/s, v_num=Maps, val_loss=3.630, train_loss=2.880]
Epoch 6: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.10it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 6:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  11%|β–ˆ         | 1/9 [00:00<00:00, 78.81it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  11%|β–ˆ         | 1/9 [00:00<00:00, 76.62it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 82.04it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 80.99it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 83.82it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 83.15it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 84.80it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 84.28it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 85.38it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.96it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 85.32it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.96it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 85.69it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 85.39it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 86.14it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.88it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 87.24it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 87.00it/s, v_num=Maps, val_loss=3.630, train_loss=2.530]
Epoch 7: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 78.37it/s, v_num=Maps, val_loss=3.110, train_loss=2.530]
Epoch 7: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.80it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 7:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.71it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  11%|β–ˆ         | 1/9 [00:00<00:00, 72.77it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.10it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 76.75it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.38it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 79.76it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.26it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 81.79it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.69it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.29it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.25it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.92it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.92it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.62it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.14it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.85it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.12it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.86it/s, v_num=Maps, val_loss=3.110, train_loss=2.020]
Epoch 8: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.42it/s, v_num=Maps, val_loss=3.020, train_loss=2.020]
Epoch 8: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.85it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 8:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  11%|β–ˆ         | 1/9 [00:00<00:00, 76.40it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.43it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.97it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.95it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 82.04it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.36it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.16it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.64it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.52it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.05it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.69it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.31it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.84it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.53it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 82.99it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 82.71it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.10it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 83.86it/s, v_num=Maps, val_loss=3.020, train_loss=1.770]
Epoch 9: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 75.85it/s, v_num=Maps, val_loss=5.580, train_loss=1.770]
Epoch 9: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 75.31it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 9:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  11%|β–ˆ         | 1/9 [00:00<00:00, 77.74it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.58it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 81.12it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 80.09it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 83.09it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 82.42it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 84.48it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.96it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 85.34it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.91it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 85.01it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.63it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.34it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.02it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.55it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.28it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.26it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.02it/s, v_num=Maps, val_loss=5.580, train_loss=1.500]
Epoch 10: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.59it/s, v_num=Maps, val_loss=2.940, train_loss=1.500]
Epoch 10: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.03it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 10:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.54it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  11%|β–ˆ         | 1/9 [00:00<00:00, 72.67it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.02it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.06it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.50it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.79it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.10it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.60it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.16it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.76it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.37it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.02it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.83it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.51it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.88it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.60it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.86it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.59it/s, v_num=Maps, val_loss=2.940, train_loss=1.700]
Epoch 11: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.21it/s, v_num=Maps, val_loss=3.700, train_loss=1.700]
Epoch 11: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.61it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 11:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.53it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  11%|β–ˆ         | 1/9 [00:00<00:00, 72.71it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.81it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.83it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.16it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.46it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.68it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.16it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.69it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.27it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.76it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.41it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.29it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 83.98it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.65it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.38it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.83it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.58it/s, v_num=Maps, val_loss=3.700, train_loss=1.290]
Epoch 12: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.91it/s, v_num=Maps, val_loss=3.200, train_loss=1.290]
Epoch 12: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.35it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 12:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.65it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.79it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.66it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.67it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.99it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.32it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.53it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.02it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.60it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.18it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.71it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.37it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 85.39it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 85.06it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.80it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.53it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.94it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.70it/s, v_num=Maps, val_loss=3.200, train_loss=1.080]
Epoch 13: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 78.27it/s, v_num=Maps, val_loss=3.290, train_loss=1.080]
Epoch 13: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.70it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 13:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  11%|β–ˆ         | 1/9 [00:00<00:00, 76.62it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.74it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 76.91it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 75.94it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 78.93it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 78.29it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.47it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 79.96it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.46it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.04it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.69it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.35it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.27it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 81.96it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 82.26it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 81.88it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 83.17it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 82.94it/s, v_num=Maps, val_loss=3.290, train_loss=1.070]
Epoch 14: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 74.88it/s, v_num=Maps, val_loss=2.670, train_loss=1.070]
Epoch 14: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 74.25it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 14:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.70it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.83it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.27it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.26it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.11it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.44it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.62it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.12it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.75it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.35it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.58it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.23it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 83.90it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 83.58it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.00it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.73it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.18it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.93it/s, v_num=Maps, val_loss=2.670, train_loss=0.804]
Epoch 15: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.72it/s, v_num=Maps, val_loss=2.610, train_loss=0.804]
Epoch 15: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.13it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 15:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  11%|β–ˆ         | 1/9 [00:00<00:00, 76.89it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.99it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.82it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.79it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.83it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.10it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.72it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.14it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 80.93it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 80.48it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 80.25it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 79.88it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 80.66it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 80.35it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 81.00it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 80.73it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 82.09it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 81.84it/s, v_num=Maps, val_loss=2.610, train_loss=0.715]
Epoch 16: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 73.69it/s, v_num=Maps, val_loss=2.500, train_loss=0.715]
Epoch 16: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 73.12it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 16:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.94it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  11%|β–ˆ         | 1/9 [00:00<00:00, 72.06it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.59it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 76.59it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 79.92it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 79.24it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 81.46it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.90it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 82.08it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.61it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.79it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.41it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.12it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 81.66it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 82.02it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 81.74it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 82.59it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 82.33it/s, v_num=Maps, val_loss=2.500, train_loss=0.698]
Epoch 17: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 74.11it/s, v_num=Maps, val_loss=3.660, train_loss=0.698]
Epoch 17: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 73.59it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 17:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.97it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  11%|β–ˆ         | 1/9 [00:00<00:00, 71.81it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.37it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.22it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.95it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.26it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.61it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.11it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.71it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.30it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.97it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.63it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.46it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.16it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.88it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.61it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.13it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.89it/s, v_num=Maps, val_loss=3.660, train_loss=0.717]
Epoch 18: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.45it/s, v_num=Maps, val_loss=2.520, train_loss=0.717]
Epoch 18: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.86it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 18:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.54it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  11%|β–ˆ         | 1/9 [00:00<00:00, 72.60it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.15it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.12it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 79.62it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 78.91it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.74it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.20it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.17it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 80.73it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.03it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 80.65it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 81.57it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 81.27it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 81.94it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 81.67it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 83.01it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 82.76it/s, v_num=Maps, val_loss=2.520, train_loss=0.797]
Epoch 19: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 74.80it/s, v_num=Maps, val_loss=2.740, train_loss=0.797]
Epoch 19: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 74.25it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 19:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.42it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.58it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.52it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.54it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.64it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.97it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.28it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.73it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.39it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.98it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.42it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.06it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.96it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.66it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.45it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.18it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.56it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.29it/s, v_num=Maps, val_loss=2.740, train_loss=0.775]
Epoch 20: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.87it/s, v_num=Maps, val_loss=3.960, train_loss=0.775]
Epoch 20: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.27it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 20:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  11%|β–ˆ         | 1/9 [00:00<00:00, 76.45it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.54it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.16it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.13it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.67it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 79.98it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 81.92it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 81.40it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 82.98it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 82.56it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.88it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.53it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 83.54it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 83.25it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.14it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.89it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.36it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.12it/s, v_num=Maps, val_loss=3.960, train_loss=0.696]
Epoch 21: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.88it/s, v_num=Maps, val_loss=2.270, train_loss=0.696]
Epoch 21: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.31it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 21:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.65it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.76it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.83it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 76.72it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 78.55it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 77.85it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 79.95it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 79.44it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.31it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 80.91it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.56it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.23it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.40it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.11it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.07it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 82.81it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.22it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 83.98it/s, v_num=Maps, val_loss=2.270, train_loss=0.747]
Epoch 22: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 75.94it/s, v_num=Maps, val_loss=2.790, train_loss=0.747]
Epoch 22: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 75.21it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 22:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  11%|β–ˆ         | 1/9 [00:00<00:00, 77.67it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.79it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 81.29it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 80.32it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 83.16it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 82.48it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 84.30it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.78it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 85.08it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.66it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 85.06it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.71it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 85.54it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 85.21it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.85it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.58it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.89it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.63it/s, v_num=Maps, val_loss=2.790, train_loss=0.833]
Epoch 23: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 78.02it/s, v_num=Maps, val_loss=2.820, train_loss=0.833]
Epoch 23: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.44it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 23:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.16it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.22it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.40it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 76.40it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 78.92it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 78.24it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.38it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 79.87it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.50it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.09it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.69it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.35it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.51it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.22it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.26it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 82.99it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.61it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.39it/s, v_num=Maps, val_loss=2.820, train_loss=0.599]
Epoch 24: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.32it/s, v_num=Maps, val_loss=2.070, train_loss=0.599]
Epoch 24: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 75.77it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 24:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  11%|β–ˆ         | 1/9 [00:00<00:00, 76.88it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.01it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.98it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.97it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.00it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.32it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 79.65it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 78.89it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 78.80it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 78.36it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 78.61it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 78.27it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 79.16it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 78.83it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 78.89it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 78.59it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 79.70it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 79.45it/s, v_num=Maps, val_loss=2.070, train_loss=0.655]
Epoch 25: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 71.70it/s, v_num=Maps, val_loss=2.660, train_loss=0.655]
Epoch 25: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 71.16it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 25:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.10it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.21it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.10it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.11it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 79.53it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 78.82it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.24it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 79.67it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 80.21it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 79.76it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 80.24it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 79.88it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 80.84it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 80.54it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 81.07it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 80.81it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 82.26it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 82.02it/s, v_num=Maps, val_loss=2.660, train_loss=1.000]
Epoch 26: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 74.29it/s, v_num=Maps, val_loss=3.090, train_loss=1.000]
Epoch 26: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 73.76it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 26:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.38it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.51it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.18it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.24it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.82it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.10it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.29it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.79it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.77it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.36it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.60it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.07it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.78it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.48it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.28it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.02it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.44it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.21it/s, v_num=Maps, val_loss=3.090, train_loss=0.695]
Epoch 27: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.11it/s, v_num=Maps, val_loss=2.160, train_loss=0.695]
Epoch 27: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 75.55it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 27:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  11%|β–ˆ         | 1/9 [00:00<00:00, 76.71it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.81it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.98it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.98it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.35it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.67it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.90it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.33it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.97it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.56it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.17it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.81it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.43it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.11it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.23it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.95it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.86it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.58it/s, v_num=Maps, val_loss=2.160, train_loss=0.786]
Epoch 28: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 75.90it/s, v_num=Maps, val_loss=1.960, train_loss=0.786]
Epoch 28: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 75.35it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 28:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.98it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.08it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.66it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.66it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 79.29it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 78.69it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.80it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.30it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.44it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.05it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.05it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 80.67it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 81.42it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 81.10it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 81.96it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 81.70it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 83.21it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 82.98it/s, v_num=Maps, val_loss=1.960, train_loss=0.594]
Epoch 29: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 75.08it/s, v_num=Maps, val_loss=2.920, train_loss=0.594]
Epoch 29: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 74.53it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 29:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.70it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  11%|β–ˆ         | 1/9 [00:00<00:00, 72.58it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.80it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 76.80it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 79.42it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 78.73it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.56it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.03it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.00it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 80.57it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.00it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 80.64it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 81.68it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 81.39it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 82.38it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 82.13it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 83.58it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 83.35it/s, v_num=Maps, val_loss=2.920, train_loss=0.593]
Epoch 30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 75.33it/s, v_num=Maps, val_loss=3.490, train_loss=0.593]
Epoch 30: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 74.77it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 30:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.72it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  11%|β–ˆ         | 1/9 [00:00<00:00, 71.94it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.90it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 76.95it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.01it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 79.30it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.42it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 79.83it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 80.00it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 79.58it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 79.33it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 78.97it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 79.75it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 79.45it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 80.43it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 80.18it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 81.95it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 81.72it/s, v_num=Maps, val_loss=3.490, train_loss=0.634]
Epoch 31: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 74.13it/s, v_num=Maps, val_loss=2.610, train_loss=0.634]
Epoch 31: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 73.61it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 31:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.85it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.04it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.33it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.39it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.39it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 79.75it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 81.64it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 81.14it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 82.02it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.62it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.20it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.88it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.87it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.59it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.33it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.09it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.43it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.19it/s, v_num=Maps, val_loss=2.610, train_loss=0.608]
Epoch 32: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.26it/s, v_num=Maps, val_loss=2.090, train_loss=0.608]
Epoch 32: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 75.69it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 32:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  11%|β–ˆ         | 1/9 [00:00<00:00, 77.06it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.16it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 80.97it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 80.01it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 82.93it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 82.25it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 84.13it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.62it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.56it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.10it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.14it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.78it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.64it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.31it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.08it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.82it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.29it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.05it/s, v_num=Maps, val_loss=2.090, train_loss=0.584]
Epoch 33: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.63it/s, v_num=Maps, val_loss=3.050, train_loss=0.584]
Epoch 33: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.06it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 33:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.37it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.32it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.94it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.96it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.94it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.27it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.43it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 81.85it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.46it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.05it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.34it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.90it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 81.65it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 81.31it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 81.73it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 81.45it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 82.49it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 82.21it/s, v_num=Maps, val_loss=3.050, train_loss=0.585]
Epoch 34: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 73.81it/s, v_num=Maps, val_loss=2.060, train_loss=0.585]
Epoch 34: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 73.23it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 34:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.71it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.90it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.57it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.57it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.09it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.36it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 81.66it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 81.12it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 82.18it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.76it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.36it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.02it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 83.19it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.88it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.93it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.67it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.28it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.06it/s, v_num=Maps, val_loss=2.060, train_loss=0.604]
Epoch 35: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.93it/s, v_num=Maps, val_loss=2.470, train_loss=0.604]
Epoch 35: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.38it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 35:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.51it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.46it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.55it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.53it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.42it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.73it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.85it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.36it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 82.35it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.94it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.88it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.55it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 83.63it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 83.34it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.12it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.86it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.00it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.76it/s, v_num=Maps, val_loss=2.470, train_loss=0.618]
Epoch 36: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.56it/s, v_num=Maps, val_loss=3.800, train_loss=0.618]
Epoch 36: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.00it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 36:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.92it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.04it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.78it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.73it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.01it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 79.27it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.79it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.25it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.47it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.06it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.81it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.47it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.72it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.44it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.49it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.24it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.83it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.61it/s, v_num=Maps, val_loss=3.800, train_loss=0.706]
Epoch 37: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.54it/s, v_num=Maps, val_loss=2.540, train_loss=0.706]
Epoch 37: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 75.95it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 37:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  11%|β–ˆ         | 1/9 [00:00<00:00, 77.94it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.97it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 80.79it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.82it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 82.81it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 82.15it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 84.11it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.60it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 85.06it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.65it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 85.33it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.99it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 85.87it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 85.56it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.95it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.66it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.80it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.53it/s, v_num=Maps, val_loss=2.540, train_loss=0.620]
Epoch 38: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.79it/s, v_num=Maps, val_loss=2.430, train_loss=0.620]
Epoch 38: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.20it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 38:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.80it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  11%|β–ˆ         | 1/9 [00:00<00:00, 72.88it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.20it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.19it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.17it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 79.48it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 81.63it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 81.12it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 82.85it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 82.44it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 83.04it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.67it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 83.75it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 83.44it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.32it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.06it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.44it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.21it/s, v_num=Maps, val_loss=2.430, train_loss=0.659]
Epoch 39: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.62it/s, v_num=Maps, val_loss=2.700, train_loss=0.659]
Epoch 39: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.08it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 39:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.65it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  11%|β–ˆ         | 1/9 [00:00<00:00, 71.94it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 78.60it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.66it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.15it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.50it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.80it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 82.30it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 84.05it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.63it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.39it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 84.06it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.97it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 84.68it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.55it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 85.29it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.57it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 86.30it/s, v_num=Maps, val_loss=2.700, train_loss=0.391]
Epoch 40: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.41it/s, v_num=Maps, val_loss=2.390, train_loss=0.391]
Epoch 40: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.84it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 40:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  11%|β–ˆ         | 1/9 [00:00<00:00, 74.02it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  11%|β–ˆ         | 1/9 [00:00<00:00, 72.17it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.63it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 76.64it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 80.05it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 79.22it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 81.21it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 80.73it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 82.58it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 82.18it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.84it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.50it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 83.68it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 83.39it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.36it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 84.10it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.67it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 85.42it/s, v_num=Maps, val_loss=2.390, train_loss=0.467]
Epoch 41: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 77.29it/s, v_num=Maps, val_loss=2.360, train_loss=0.467]
Epoch 41: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.70it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 41:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  11%|β–ˆ         | 1/9 [00:00<00:00, 73.11it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  11%|β–ˆ         | 1/9 [00:00<00:00, 71.33it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 77.10it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 75.67it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 77.58it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 76.98it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 79.67it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 79.17it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 81.17it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 80.78it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.64it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 81.32it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.62it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.34it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.41it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 83.16it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.65it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 84.39it/s, v_num=Maps, val_loss=2.360, train_loss=0.441]
Epoch 42: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 76.17it/s, v_num=Maps, val_loss=2.840, train_loss=0.441]
Epoch 42: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 75.59it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 42:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:   0%|          | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  11%|β–ˆ         | 1/9 [00:00<00:00, 77.87it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  11%|β–ˆ         | 1/9 [00:00<00:00, 75.97it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 80.71it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  22%|β–ˆβ–ˆβ–       | 2/9 [00:00<00:00, 79.70it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 82.56it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  33%|β–ˆβ–ˆβ–ˆβ–Ž      | 3/9 [00:00<00:00, 81.88it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.87it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  44%|β–ˆβ–ˆβ–ˆβ–ˆβ–     | 4/9 [00:00<00:00, 83.36it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 83.23it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ    | 5/9 [00:00<00:00, 82.78it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.54it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹   | 6/9 [00:00<00:00, 82.18it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 83.01it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š  | 7/9 [00:00<00:00, 82.69it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 79.72it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43:  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 8/9 [00:00<00:00, 79.34it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 80.81it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 80.59it/s, v_num=Maps, val_loss=2.840, train_loss=0.515]
Epoch 43: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 73.05it/s, v_num=Maps, val_loss=2.500, train_loss=0.515]
Epoch 43: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 72.54it/s, v_num=Maps, val_loss=2.500, train_loss=0.458]
Epoch 43: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 9/9 [00:00<00:00, 63.18it/s, v_num=Maps, val_loss=2.500, train_loss=0.458]
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
     Validate metric           DataLoader 0
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
         MAE_val            1.0378193855285645
         R2_val             0.6757254600524902
        val_loss            2.5035037994384766
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────

Evaluating with validation data

We’ll start by evaluating the model with the validation data.

reals_preds_validation = RealsVsPreds.from_final_val_data(trained_model)
plt.show()
Evaluation: Validation Data, Concatenating tabular feature maps - Validation R2: 0.676

Evaluating with external data

Now we’ll evaluate the model with the external data.

reals_preds_external = RealsVsPreds.from_new_data(trained_model,
                                                  output_paths=output_paths,
                                                  test_data_paths=external_data_paths)
plt.show()
Evaluation: External Test Data, Concatenating tabular feature maps - Validation r2: 0.429

Removing checkpoint files

for dir in os.listdir(output_paths["checkpoints"]):
    # remove files
    os.remove(os.path.join(output_paths["checkpoints"], dir))

Total running time of the script: (0 minutes 6.949 seconds)

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