Note
Go to the end to download the full example code.
Using External Test Dataο
Letβs 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.
Weβll 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,
)
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 | 1/9 [00:00<00:00, 80.65it/s]
Epoch 0: 11%|β | 1/9 [00:00<00:00, 79.18it/s, v_num=Maps]
Epoch 0: 22%|βββ | 2/9 [00:00<00:00, 86.87it/s, v_num=Maps]
Epoch 0: 22%|βββ | 2/9 [00:00<00:00, 86.10it/s, v_num=Maps]
Epoch 0: 33%|ββββ | 3/9 [00:00<00:00, 90.51it/s, v_num=Maps]
Epoch 0: 33%|ββββ | 3/9 [00:00<00:00, 89.98it/s, v_num=Maps]
Epoch 0: 44%|βββββ | 4/9 [00:00<00:00, 92.46it/s, v_num=Maps]
Epoch 0: 44%|βββββ | 4/9 [00:00<00:00, 92.05it/s, v_num=Maps]
Epoch 0: 56%|ββββββ | 5/9 [00:00<00:00, 94.19it/s, v_num=Maps]
Epoch 0: 56%|ββββββ | 5/9 [00:00<00:00, 93.86it/s, v_num=Maps]
Epoch 0: 67%|βββββββ | 6/9 [00:00<00:00, 94.83it/s, v_num=Maps]
Epoch 0: 67%|βββββββ | 6/9 [00:00<00:00, 94.55it/s, v_num=Maps]
Epoch 0: 78%|ββββββββ | 7/9 [00:00<00:00, 95.86it/s, v_num=Maps]
Epoch 0: 78%|ββββββββ | 7/9 [00:00<00:00, 95.61it/s, v_num=Maps]
Epoch 0: 89%|βββββββββ | 8/9 [00:00<00:00, 96.56it/s, v_num=Maps]
Epoch 0: 89%|βββββββββ | 8/9 [00:00<00:00, 96.34it/s, v_num=Maps]
Epoch 0: 100%|ββββββββββ| 9/9 [00:00<00:00, 97.89it/s, v_num=Maps]
Epoch 0: 100%|ββββββββββ| 9/9 [00:00<00:00, 97.70it/s, v_num=Maps]
Epoch 0: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.12it/s, v_num=Maps, val_loss=9.850]
Epoch 0: 100%|ββββββββββ| 9/9 [00:00<00:00, 86.58it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 0: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 11%|β | 1/9 [00:00<00:00, 92.00it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 11%|β | 1/9 [00:00<00:00, 90.29it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 22%|βββ | 2/9 [00:00<00:00, 94.71it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 22%|βββ | 2/9 [00:00<00:00, 93.79it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 33%|ββββ | 3/9 [00:00<00:00, 96.31it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 33%|ββββ | 3/9 [00:00<00:00, 95.69it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 44%|βββββ | 4/9 [00:00<00:00, 97.22it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 44%|βββββ | 4/9 [00:00<00:00, 96.75it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 56%|ββββββ | 5/9 [00:00<00:00, 97.27it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 56%|ββββββ | 5/9 [00:00<00:00, 96.81it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 67%|βββββββ | 6/9 [00:00<00:00, 97.29it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 67%|βββββββ | 6/9 [00:00<00:00, 96.93it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 78%|ββββββββ | 7/9 [00:00<00:00, 97.88it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 78%|ββββββββ | 7/9 [00:00<00:00, 97.58it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 89%|βββββββββ | 8/9 [00:00<00:00, 98.16it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 89%|βββββββββ | 8/9 [00:00<00:00, 97.89it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.09it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.87it/s, v_num=Maps, val_loss=9.850, train_loss=13.30]
Epoch 1: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.87it/s, v_num=Maps, val_loss=6.070, train_loss=13.30]
Epoch 1: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.32it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 1: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 11%|β | 1/9 [00:00<00:00, 95.49it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 11%|β | 1/9 [00:00<00:00, 93.64it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 22%|βββ | 2/9 [00:00<00:00, 97.29it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 22%|βββ | 2/9 [00:00<00:00, 96.33it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 33%|ββββ | 3/9 [00:00<00:00, 98.32it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 33%|ββββ | 3/9 [00:00<00:00, 97.66it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 44%|βββββ | 4/9 [00:00<00:00, 97.35it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 44%|βββββ | 4/9 [00:00<00:00, 96.79it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 56%|ββββββ | 5/9 [00:00<00:00, 97.95it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 56%|ββββββ | 5/9 [00:00<00:00, 97.56it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 67%|βββββββ | 6/9 [00:00<00:00, 98.31it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 67%|βββββββ | 6/9 [00:00<00:00, 97.95it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 78%|ββββββββ | 7/9 [00:00<00:00, 98.68it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 78%|ββββββββ | 7/9 [00:00<00:00, 98.40it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 89%|βββββββββ | 8/9 [00:00<00:00, 98.32it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 89%|βββββββββ | 8/9 [00:00<00:00, 98.08it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.26it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.04it/s, v_num=Maps, val_loss=6.070, train_loss=7.780]
Epoch 2: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.25it/s, v_num=Maps, val_loss=4.630, train_loss=7.780]
Epoch 2: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.71it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 2: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 11%|β | 1/9 [00:00<00:00, 89.57it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 11%|β | 1/9 [00:00<00:00, 87.67it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 22%|βββ | 2/9 [00:00<00:00, 92.33it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 22%|βββ | 2/9 [00:00<00:00, 91.37it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 33%|ββββ | 3/9 [00:00<00:00, 93.82it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 33%|ββββ | 3/9 [00:00<00:00, 93.23it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 44%|βββββ | 4/9 [00:00<00:00, 94.90it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 44%|βββββ | 4/9 [00:00<00:00, 94.44it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 56%|ββββββ | 5/9 [00:00<00:00, 95.44it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 56%|ββββββ | 5/9 [00:00<00:00, 95.06it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 67%|βββββββ | 6/9 [00:00<00:00, 95.99it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 67%|βββββββ | 6/9 [00:00<00:00, 95.65it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 78%|ββββββββ | 7/9 [00:00<00:00, 96.67it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 78%|ββββββββ | 7/9 [00:00<00:00, 96.40it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 89%|βββββββββ | 8/9 [00:00<00:00, 97.22it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 89%|βββββββββ | 8/9 [00:00<00:00, 96.98it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.01it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 100%|ββββββββββ| 9/9 [00:00<00:00, 97.79it/s, v_num=Maps, val_loss=4.630, train_loss=6.120]
Epoch 3: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.72it/s, v_num=Maps, val_loss=4.000, train_loss=6.120]
Epoch 3: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.19it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 3: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 11%|β | 1/9 [00:00<00:00, 92.02it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 11%|β | 1/9 [00:00<00:00, 90.23it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 22%|βββ | 2/9 [00:00<00:00, 93.93it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 22%|βββ | 2/9 [00:00<00:00, 93.00it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 33%|ββββ | 3/9 [00:00<00:00, 95.24it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 33%|ββββ | 3/9 [00:00<00:00, 94.62it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 44%|βββββ | 4/9 [00:00<00:00, 95.92it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 44%|βββββ | 4/9 [00:00<00:00, 95.44it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 56%|ββββββ | 5/9 [00:00<00:00, 96.79it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 56%|ββββββ | 5/9 [00:00<00:00, 96.41it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 67%|βββββββ | 6/9 [00:00<00:00, 97.47it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 67%|βββββββ | 6/9 [00:00<00:00, 97.15it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 78%|ββββββββ | 7/9 [00:00<00:00, 98.17it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 78%|ββββββββ | 7/9 [00:00<00:00, 97.88it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 89%|βββββββββ | 8/9 [00:00<00:00, 98.03it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 89%|βββββββββ | 8/9 [00:00<00:00, 97.78it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.25it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.02it/s, v_num=Maps, val_loss=4.000, train_loss=4.530]
Epoch 4: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.87it/s, v_num=Maps, val_loss=3.990, train_loss=4.530]
Epoch 4: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.35it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 4: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 11%|β | 1/9 [00:00<00:00, 94.83it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 11%|β | 1/9 [00:00<00:00, 92.98it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 22%|βββ | 2/9 [00:00<00:00, 96.79it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 22%|βββ | 2/9 [00:00<00:00, 95.70it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 33%|ββββ | 3/9 [00:00<00:00, 97.93it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 33%|ββββ | 3/9 [00:00<00:00, 97.22it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 44%|βββββ | 4/9 [00:00<00:00, 98.61it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 44%|βββββ | 4/9 [00:00<00:00, 98.12it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 56%|ββββββ | 5/9 [00:00<00:00, 98.62it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 56%|ββββββ | 5/9 [00:00<00:00, 98.19it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 67%|βββββββ | 6/9 [00:00<00:00, 98.92it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 67%|βββββββ | 6/9 [00:00<00:00, 98.55it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 78%|ββββββββ | 7/9 [00:00<00:00, 98.79it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 78%|ββββββββ | 7/9 [00:00<00:00, 98.50it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 89%|βββββββββ | 8/9 [00:00<00:00, 98.74it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 89%|βββββββββ | 8/9 [00:00<00:00, 98.49it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.50it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.28it/s, v_num=Maps, val_loss=3.990, train_loss=3.260]
Epoch 5: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.98it/s, v_num=Maps, val_loss=5.150, train_loss=3.260]
Epoch 5: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.45it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 5: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 11%|β | 1/9 [00:00<00:00, 91.52it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 11%|β | 1/9 [00:00<00:00, 89.65it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 22%|βββ | 2/9 [00:00<00:00, 95.01it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 22%|βββ | 2/9 [00:00<00:00, 94.00it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 33%|ββββ | 3/9 [00:00<00:00, 96.14it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 33%|ββββ | 3/9 [00:00<00:00, 95.51it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 44%|βββββ | 4/9 [00:00<00:00, 95.84it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 44%|βββββ | 4/9 [00:00<00:00, 95.36it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 56%|ββββββ | 5/9 [00:00<00:00, 96.31it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 56%|ββββββ | 5/9 [00:00<00:00, 95.86it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 67%|βββββββ | 6/9 [00:00<00:00, 96.68it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 67%|βββββββ | 6/9 [00:00<00:00, 96.33it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 78%|ββββββββ | 7/9 [00:00<00:00, 97.10it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 78%|ββββββββ | 7/9 [00:00<00:00, 96.80it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 89%|βββββββββ | 8/9 [00:00<00:00, 97.06it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 89%|βββββββββ | 8/9 [00:00<00:00, 96.83it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.31it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.10it/s, v_num=Maps, val_loss=5.150, train_loss=2.960]
Epoch 6: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.06it/s, v_num=Maps, val_loss=4.450, train_loss=2.960]
Epoch 6: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.54it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 6: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 11%|β | 1/9 [00:00<00:00, 91.21it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 11%|β | 1/9 [00:00<00:00, 89.28it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 22%|βββ | 2/9 [00:00<00:00, 94.33it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 22%|βββ | 2/9 [00:00<00:00, 93.42it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 33%|ββββ | 3/9 [00:00<00:00, 96.01it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 33%|ββββ | 3/9 [00:00<00:00, 95.38it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 44%|βββββ | 4/9 [00:00<00:00, 96.28it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 44%|βββββ | 4/9 [00:00<00:00, 95.81it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 56%|ββββββ | 5/9 [00:00<00:00, 96.43it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 56%|ββββββ | 5/9 [00:00<00:00, 96.05it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 67%|βββββββ | 6/9 [00:00<00:00, 97.13it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 67%|βββββββ | 6/9 [00:00<00:00, 96.81it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 78%|ββββββββ | 7/9 [00:00<00:00, 97.62it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 78%|ββββββββ | 7/9 [00:00<00:00, 97.34it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 89%|βββββββββ | 8/9 [00:00<00:00, 98.24it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 89%|βββββββββ | 8/9 [00:00<00:00, 98.00it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.05it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.83it/s, v_num=Maps, val_loss=4.450, train_loss=2.590]
Epoch 7: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.81it/s, v_num=Maps, val_loss=4.590, train_loss=2.590]
Epoch 7: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.28it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 7: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 11%|β | 1/9 [00:00<00:00, 96.68it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 11%|β | 1/9 [00:00<00:00, 94.78it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 22%|βββ | 2/9 [00:00<00:00, 98.28it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 22%|βββ | 2/9 [00:00<00:00, 97.30it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 33%|ββββ | 3/9 [00:00<00:00, 99.11it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 33%|ββββ | 3/9 [00:00<00:00, 98.44it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 44%|βββββ | 4/9 [00:00<00:00, 98.89it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 44%|βββββ | 4/9 [00:00<00:00, 98.40it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 56%|ββββββ | 5/9 [00:00<00:00, 99.45it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 56%|ββββββ | 5/9 [00:00<00:00, 99.05it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 67%|βββββββ | 6/9 [00:00<00:00, 99.67it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 67%|βββββββ | 6/9 [00:00<00:00, 99.30it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 78%|ββββββββ | 7/9 [00:00<00:00, 99.71it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 78%|ββββββββ | 7/9 [00:00<00:00, 99.40it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 89%|βββββββββ | 8/9 [00:00<00:00, 99.71it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 89%|βββββββββ | 8/9 [00:00<00:00, 99.43it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.73it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.50it/s, v_num=Maps, val_loss=4.590, train_loss=2.100]
Epoch 8: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.14it/s, v_num=Maps, val_loss=4.310, train_loss=2.100]
Epoch 8: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.57it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 8: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 11%|β | 1/9 [00:00<00:00, 96.69it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 11%|β | 1/9 [00:00<00:00, 94.79it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 22%|βββ | 2/9 [00:00<00:00, 98.53it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 22%|βββ | 2/9 [00:00<00:00, 97.55it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 33%|ββββ | 3/9 [00:00<00:00, 98.48it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 33%|ββββ | 3/9 [00:00<00:00, 97.76it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 44%|βββββ | 4/9 [00:00<00:00, 99.00it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 44%|βββββ | 4/9 [00:00<00:00, 98.46it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 56%|ββββββ | 5/9 [00:00<00:00, 99.12it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 56%|ββββββ | 5/9 [00:00<00:00, 98.68it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 67%|βββββββ | 6/9 [00:00<00:00, 99.30it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 67%|βββββββ | 6/9 [00:00<00:00, 98.91it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 78%|ββββββββ | 7/9 [00:00<00:00, 99.60it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 78%|ββββββββ | 7/9 [00:00<00:00, 99.31it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 89%|βββββββββ | 8/9 [00:00<00:00, 99.69it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 89%|βββββββββ | 8/9 [00:00<00:00, 99.44it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.52it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.27it/s, v_num=Maps, val_loss=4.310, train_loss=1.970]
Epoch 9: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.84it/s, v_num=Maps, val_loss=3.640, train_loss=1.970]
Epoch 9: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.27it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 9: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 11%|β | 1/9 [00:00<00:00, 92.90it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 11%|β | 1/9 [00:00<00:00, 91.09it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 22%|βββ | 2/9 [00:00<00:00, 95.53it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 22%|βββ | 2/9 [00:00<00:00, 94.60it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 33%|ββββ | 3/9 [00:00<00:00, 96.96it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 33%|ββββ | 3/9 [00:00<00:00, 96.33it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 44%|βββββ | 4/9 [00:00<00:00, 96.97it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 44%|βββββ | 4/9 [00:00<00:00, 96.45it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 56%|ββββββ | 5/9 [00:00<00:00, 97.63it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 56%|ββββββ | 5/9 [00:00<00:00, 97.20it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 67%|βββββββ | 6/9 [00:00<00:00, 98.13it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 67%|βββββββ | 6/9 [00:00<00:00, 97.78it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 78%|ββββββββ | 7/9 [00:00<00:00, 98.49it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 78%|ββββββββ | 7/9 [00:00<00:00, 98.21it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 89%|βββββββββ | 8/9 [00:00<00:00, 98.47it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 89%|βββββββββ | 8/9 [00:00<00:00, 98.20it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.70it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.45it/s, v_num=Maps, val_loss=3.640, train_loss=1.600]
Epoch 10: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.17it/s, v_num=Maps, val_loss=3.840, train_loss=1.600]
Epoch 10: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.61it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 10: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 11%|β | 1/9 [00:00<00:00, 94.08it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 11%|β | 1/9 [00:00<00:00, 92.28it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 22%|βββ | 2/9 [00:00<00:00, 96.22it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 22%|βββ | 2/9 [00:00<00:00, 95.28it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 33%|ββββ | 3/9 [00:00<00:00, 97.35it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 33%|ββββ | 3/9 [00:00<00:00, 96.71it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 44%|βββββ | 4/9 [00:00<00:00, 98.05it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 44%|βββββ | 4/9 [00:00<00:00, 97.57it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 56%|ββββββ | 5/9 [00:00<00:00, 98.14it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 56%|ββββββ | 5/9 [00:00<00:00, 97.75it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 67%|βββββββ | 6/9 [00:00<00:00, 98.57it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 67%|βββββββ | 6/9 [00:00<00:00, 98.24it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 78%|ββββββββ | 7/9 [00:00<00:00, 99.16it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 78%|ββββββββ | 7/9 [00:00<00:00, 98.88it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 89%|βββββββββ | 8/9 [00:00<00:00, 99.33it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 89%|βββββββββ | 8/9 [00:00<00:00, 99.08it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.66it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.41it/s, v_num=Maps, val_loss=3.840, train_loss=1.220]
Epoch 11: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.84it/s, v_num=Maps, val_loss=3.770, train_loss=1.220]
Epoch 11: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.26it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 11: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 11%|β | 1/9 [00:00<00:00, 95.05it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 11%|β | 1/9 [00:00<00:00, 93.20it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 22%|βββ | 2/9 [00:00<00:00, 96.93it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 22%|βββ | 2/9 [00:00<00:00, 95.97it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 33%|ββββ | 3/9 [00:00<00:00, 98.10it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 33%|ββββ | 3/9 [00:00<00:00, 97.45it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 44%|βββββ | 4/9 [00:00<00:00, 98.04it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 44%|βββββ | 4/9 [00:00<00:00, 97.52it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 56%|ββββββ | 5/9 [00:00<00:00, 98.56it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 56%|ββββββ | 5/9 [00:00<00:00, 98.16it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 67%|βββββββ | 6/9 [00:00<00:00, 99.01it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 67%|βββββββ | 6/9 [00:00<00:00, 98.67it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 78%|ββββββββ | 7/9 [00:00<00:00, 98.63it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 78%|ββββββββ | 7/9 [00:00<00:00, 98.32it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 89%|βββββββββ | 8/9 [00:00<00:00, 98.41it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 89%|βββββββββ | 8/9 [00:00<00:00, 98.17it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.46it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.24it/s, v_num=Maps, val_loss=3.770, train_loss=1.050]
Epoch 12: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.93it/s, v_num=Maps, val_loss=3.780, train_loss=1.050]
Epoch 12: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.39it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 12: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 11%|β | 1/9 [00:00<00:00, 95.82it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 11%|β | 1/9 [00:00<00:00, 93.91it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 22%|βββ | 2/9 [00:00<00:00, 98.25it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 22%|βββ | 2/9 [00:00<00:00, 97.27it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 33%|ββββ | 3/9 [00:00<00:00, 99.07it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 33%|ββββ | 3/9 [00:00<00:00, 98.41it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 44%|βββββ | 4/9 [00:00<00:00, 99.81it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 44%|βββββ | 4/9 [00:00<00:00, 99.26it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 56%|ββββββ | 5/9 [00:00<00:00, 99.76it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 56%|ββββββ | 5/9 [00:00<00:00, 99.32it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 67%|βββββββ | 6/9 [00:00<00:00, 100.04it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 67%|βββββββ | 6/9 [00:00<00:00, 99.67it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 78%|ββββββββ | 7/9 [00:00<00:00, 100.50it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 78%|ββββββββ | 7/9 [00:00<00:00, 100.20it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 89%|βββββββββ | 8/9 [00:00<00:00, 100.56it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 89%|βββββββββ | 8/9 [00:00<00:00, 100.30it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.19it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.96it/s, v_num=Maps, val_loss=3.780, train_loss=0.998]
Epoch 13: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.49it/s, v_num=Maps, val_loss=3.950, train_loss=0.998]
Epoch 13: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.92it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 13: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 11%|β | 1/9 [00:00<00:00, 94.55it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 11%|β | 1/9 [00:00<00:00, 92.49it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 22%|βββ | 2/9 [00:00<00:00, 97.23it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 22%|βββ | 2/9 [00:00<00:00, 96.16it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 33%|ββββ | 3/9 [00:00<00:00, 98.04it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 33%|ββββ | 3/9 [00:00<00:00, 97.32it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 44%|βββββ | 4/9 [00:00<00:00, 98.36it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 44%|βββββ | 4/9 [00:00<00:00, 97.83it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 56%|ββββββ | 5/9 [00:00<00:00, 99.05it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 56%|ββββββ | 5/9 [00:00<00:00, 98.65it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 67%|βββββββ | 6/9 [00:00<00:00, 99.36it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 67%|βββββββ | 6/9 [00:00<00:00, 99.03it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 78%|ββββββββ | 7/9 [00:00<00:00, 99.78it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 78%|ββββββββ | 7/9 [00:00<00:00, 99.49it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 89%|βββββββββ | 8/9 [00:00<00:00, 99.67it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 89%|βββββββββ | 8/9 [00:00<00:00, 99.42it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.81it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.58it/s, v_num=Maps, val_loss=3.950, train_loss=0.925]
Epoch 14: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.22it/s, v_num=Maps, val_loss=3.920, train_loss=0.925]
Epoch 14: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.67it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 14: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 11%|β | 1/9 [00:00<00:00, 92.21it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 11%|β | 1/9 [00:00<00:00, 90.42it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 22%|βββ | 2/9 [00:00<00:00, 95.73it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 22%|βββ | 2/9 [00:00<00:00, 94.79it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 33%|ββββ | 3/9 [00:00<00:00, 97.33it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 33%|ββββ | 3/9 [00:00<00:00, 96.69it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 44%|βββββ | 4/9 [00:00<00:00, 98.48it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 44%|βββββ | 4/9 [00:00<00:00, 97.98it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 56%|ββββββ | 5/9 [00:00<00:00, 98.51it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 56%|ββββββ | 5/9 [00:00<00:00, 98.11it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 67%|βββββββ | 6/9 [00:00<00:00, 98.77it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 67%|βββββββ | 6/9 [00:00<00:00, 98.44it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 78%|ββββββββ | 7/9 [00:00<00:00, 99.27it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 78%|ββββββββ | 7/9 [00:00<00:00, 98.99it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 89%|βββββββββ | 8/9 [00:00<00:00, 99.61it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 89%|βββββββββ | 8/9 [00:00<00:00, 99.33it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.39it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.16it/s, v_num=Maps, val_loss=3.920, train_loss=0.944]
Epoch 15: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.81it/s, v_num=Maps, val_loss=3.860, train_loss=0.944]
Epoch 15: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.25it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 15: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 11%|β | 1/9 [00:00<00:00, 95.28it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 11%|β | 1/9 [00:00<00:00, 93.20it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 22%|βββ | 2/9 [00:00<00:00, 97.58it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 22%|βββ | 2/9 [00:00<00:00, 96.31it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 33%|ββββ | 3/9 [00:00<00:00, 99.01it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 33%|ββββ | 3/9 [00:00<00:00, 98.35it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 44%|βββββ | 4/9 [00:00<00:00, 99.11it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 44%|βββββ | 4/9 [00:00<00:00, 98.52it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 56%|ββββββ | 5/9 [00:00<00:00, 99.52it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 56%|ββββββ | 5/9 [00:00<00:00, 99.12it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 67%|βββββββ | 6/9 [00:00<00:00, 99.84it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 67%|βββββββ | 6/9 [00:00<00:00, 99.50it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 78%|ββββββββ | 7/9 [00:00<00:00, 100.17it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 78%|ββββββββ | 7/9 [00:00<00:00, 99.87it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 89%|βββββββββ | 8/9 [00:00<00:00, 100.15it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 89%|βββββββββ | 8/9 [00:00<00:00, 99.89it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.20it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.97it/s, v_num=Maps, val_loss=3.860, train_loss=0.720]
Epoch 16: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.53it/s, v_num=Maps, val_loss=4.120, train_loss=0.720]
Epoch 16: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.96it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 16: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 11%|β | 1/9 [00:00<00:00, 94.56it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 11%|β | 1/9 [00:00<00:00, 92.71it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 22%|βββ | 2/9 [00:00<00:00, 97.23it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 22%|βββ | 2/9 [00:00<00:00, 96.26it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 33%|ββββ | 3/9 [00:00<00:00, 98.42it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 33%|ββββ | 3/9 [00:00<00:00, 97.76it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 44%|βββββ | 4/9 [00:00<00:00, 99.26it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 44%|βββββ | 4/9 [00:00<00:00, 98.71it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 56%|ββββββ | 5/9 [00:00<00:00, 99.03it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 56%|ββββββ | 5/9 [00:00<00:00, 98.64it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 67%|βββββββ | 6/9 [00:00<00:00, 99.55it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 67%|βββββββ | 6/9 [00:00<00:00, 99.19it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 78%|ββββββββ | 7/9 [00:00<00:00, 99.83it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 78%|ββββββββ | 7/9 [00:00<00:00, 99.52it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 89%|βββββββββ | 8/9 [00:00<00:00, 99.98it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 89%|βββββββββ | 8/9 [00:00<00:00, 99.73it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.84it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.59it/s, v_num=Maps, val_loss=4.120, train_loss=0.668]
Epoch 17: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.15it/s, v_num=Maps, val_loss=3.580, train_loss=0.668]
Epoch 17: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.59it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 17: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 11%|β | 1/9 [00:00<00:00, 94.75it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 11%|β | 1/9 [00:00<00:00, 92.89it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 22%|βββ | 2/9 [00:00<00:00, 96.40it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 22%|βββ | 2/9 [00:00<00:00, 95.43it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 33%|ββββ | 3/9 [00:00<00:00, 98.10it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 33%|ββββ | 3/9 [00:00<00:00, 97.44it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 44%|βββββ | 4/9 [00:00<00:00, 98.45it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 44%|βββββ | 4/9 [00:00<00:00, 97.95it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 56%|ββββββ | 5/9 [00:00<00:00, 99.10it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 56%|ββββββ | 5/9 [00:00<00:00, 98.71it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 67%|βββββββ | 6/9 [00:00<00:00, 99.63it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 67%|βββββββ | 6/9 [00:00<00:00, 99.26it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 78%|ββββββββ | 7/9 [00:00<00:00, 99.94it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 78%|ββββββββ | 7/9 [00:00<00:00, 99.66it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 89%|βββββββββ | 8/9 [00:00<00:00, 99.94it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 89%|βββββββββ | 8/9 [00:00<00:00, 99.66it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.08it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.85it/s, v_num=Maps, val_loss=3.580, train_loss=0.707]
Epoch 18: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.45it/s, v_num=Maps, val_loss=3.800, train_loss=0.707]
Epoch 18: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.90it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 18: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 11%|β | 1/9 [00:00<00:00, 95.71it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 11%|β | 1/9 [00:00<00:00, 93.79it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 22%|βββ | 2/9 [00:00<00:00, 97.77it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 22%|βββ | 2/9 [00:00<00:00, 96.78it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 33%|ββββ | 3/9 [00:00<00:00, 98.51it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 33%|ββββ | 3/9 [00:00<00:00, 97.84it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 44%|βββββ | 4/9 [00:00<00:00, 99.37it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 44%|βββββ | 4/9 [00:00<00:00, 98.82it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 56%|ββββββ | 5/9 [00:00<00:00, 98.62it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 56%|ββββββ | 5/9 [00:00<00:00, 98.23it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 67%|βββββββ | 6/9 [00:00<00:00, 97.98it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 67%|βββββββ | 6/9 [00:00<00:00, 97.55it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 78%|ββββββββ | 7/9 [00:00<00:00, 98.12it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 78%|ββββββββ | 7/9 [00:00<00:00, 97.80it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 89%|βββββββββ | 8/9 [00:00<00:00, 98.42it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 89%|βββββββββ | 8/9 [00:00<00:00, 98.14it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.78it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.55it/s, v_num=Maps, val_loss=3.800, train_loss=0.690]
Epoch 19: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.89it/s, v_num=Maps, val_loss=3.620, train_loss=0.690]
Epoch 19: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.34it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 19: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 11%|β | 1/9 [00:00<00:00, 89.93it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 11%|β | 1/9 [00:00<00:00, 88.17it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 22%|βββ | 2/9 [00:00<00:00, 92.31it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 22%|βββ | 2/9 [00:00<00:00, 91.33it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 33%|ββββ | 3/9 [00:00<00:00, 94.78it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 33%|ββββ | 3/9 [00:00<00:00, 94.04it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 44%|βββββ | 4/9 [00:00<00:00, 95.92it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 44%|βββββ | 4/9 [00:00<00:00, 95.40it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 56%|ββββββ | 5/9 [00:00<00:00, 96.37it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 56%|ββββββ | 5/9 [00:00<00:00, 96.00it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 67%|βββββββ | 6/9 [00:00<00:00, 96.86it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 67%|βββββββ | 6/9 [00:00<00:00, 96.54it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 78%|ββββββββ | 7/9 [00:00<00:00, 97.24it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 78%|ββββββββ | 7/9 [00:00<00:00, 96.96it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 89%|βββββββββ | 8/9 [00:00<00:00, 97.30it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 89%|βββββββββ | 8/9 [00:00<00:00, 97.06it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.48it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.27it/s, v_num=Maps, val_loss=3.620, train_loss=0.687]
Epoch 20: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.03it/s, v_num=Maps, val_loss=3.710, train_loss=0.687]
Epoch 20: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.48it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 20: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 11%|β | 1/9 [00:00<00:00, 88.69it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 11%|β | 1/9 [00:00<00:00, 86.92it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 22%|βββ | 2/9 [00:00<00:00, 92.79it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 22%|βββ | 2/9 [00:00<00:00, 91.86it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 33%|ββββ | 3/9 [00:00<00:00, 94.60it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 33%|ββββ | 3/9 [00:00<00:00, 93.99it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 44%|βββββ | 4/9 [00:00<00:00, 95.92it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 44%|βββββ | 4/9 [00:00<00:00, 95.44it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 56%|ββββββ | 5/9 [00:00<00:00, 96.42it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 56%|ββββββ | 5/9 [00:00<00:00, 96.01it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 67%|βββββββ | 6/9 [00:00<00:00, 97.14it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 67%|βββββββ | 6/9 [00:00<00:00, 96.83it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 78%|ββββββββ | 7/9 [00:00<00:00, 97.73it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 78%|ββββββββ | 7/9 [00:00<00:00, 97.45it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 89%|βββββββββ | 8/9 [00:00<00:00, 98.23it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 89%|βββββββββ | 8/9 [00:00<00:00, 97.98it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.83it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.60it/s, v_num=Maps, val_loss=3.710, train_loss=0.756]
Epoch 21: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.55it/s, v_num=Maps, val_loss=3.530, train_loss=0.756]
Epoch 21: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.00it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 21: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 11%|β | 1/9 [00:00<00:00, 95.99it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 11%|β | 1/9 [00:00<00:00, 94.02it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 22%|βββ | 2/9 [00:00<00:00, 98.05it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 22%|βββ | 2/9 [00:00<00:00, 97.06it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 33%|ββββ | 3/9 [00:00<00:00, 98.88it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 33%|ββββ | 3/9 [00:00<00:00, 97.98it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 44%|βββββ | 4/9 [00:00<00:00, 96.95it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 44%|βββββ | 4/9 [00:00<00:00, 96.45it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 56%|ββββββ | 5/9 [00:00<00:00, 96.61it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 56%|ββββββ | 5/9 [00:00<00:00, 96.20it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 67%|βββββββ | 6/9 [00:00<00:00, 96.55it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 67%|βββββββ | 6/9 [00:00<00:00, 96.22it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 78%|ββββββββ | 7/9 [00:00<00:00, 96.89it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 78%|ββββββββ | 7/9 [00:00<00:00, 96.62it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 89%|βββββββββ | 8/9 [00:00<00:00, 96.63it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 89%|βββββββββ | 8/9 [00:00<00:00, 96.32it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 100%|ββββββββββ| 9/9 [00:00<00:00, 97.51it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 100%|ββββββββββ| 9/9 [00:00<00:00, 97.30it/s, v_num=Maps, val_loss=3.530, train_loss=0.653]
Epoch 22: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.24it/s, v_num=Maps, val_loss=3.390, train_loss=0.653]
Epoch 22: 100%|ββββββββββ| 9/9 [00:00<00:00, 86.71it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 22: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 11%|β | 1/9 [00:00<00:00, 89.75it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 11%|β | 1/9 [00:00<00:00, 88.01it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 22%|βββ | 2/9 [00:00<00:00, 93.39it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 22%|βββ | 2/9 [00:00<00:00, 92.49it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 33%|ββββ | 3/9 [00:00<00:00, 95.25it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 33%|ββββ | 3/9 [00:00<00:00, 94.57it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 44%|βββββ | 4/9 [00:00<00:00, 95.78it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 44%|βββββ | 4/9 [00:00<00:00, 95.32it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 56%|ββββββ | 5/9 [00:00<00:00, 95.67it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 56%|ββββββ | 5/9 [00:00<00:00, 95.29it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 67%|βββββββ | 6/9 [00:00<00:00, 96.46it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 67%|βββββββ | 6/9 [00:00<00:00, 96.15it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 78%|ββββββββ | 7/9 [00:00<00:00, 96.89it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 78%|ββββββββ | 7/9 [00:00<00:00, 96.62it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 89%|βββββββββ | 8/9 [00:00<00:00, 97.28it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 89%|βββββββββ | 8/9 [00:00<00:00, 97.04it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 100%|ββββββββββ| 9/9 [00:00<00:00, 97.90it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 100%|ββββββββββ| 9/9 [00:00<00:00, 97.68it/s, v_num=Maps, val_loss=3.390, train_loss=0.614]
Epoch 23: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.77it/s, v_num=Maps, val_loss=3.510, train_loss=0.614]
Epoch 23: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.23it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 23: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 11%|β | 1/9 [00:00<00:00, 93.14it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 11%|β | 1/9 [00:00<00:00, 90.09it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 22%|βββ | 2/9 [00:00<00:00, 95.14it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 22%|βββ | 2/9 [00:00<00:00, 94.22it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 33%|ββββ | 3/9 [00:00<00:00, 96.65it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 33%|ββββ | 3/9 [00:00<00:00, 96.02it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 44%|βββββ | 4/9 [00:00<00:00, 96.79it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 44%|βββββ | 4/9 [00:00<00:00, 96.24it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 56%|ββββββ | 5/9 [00:00<00:00, 97.61it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 56%|ββββββ | 5/9 [00:00<00:00, 97.23it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 67%|βββββββ | 6/9 [00:00<00:00, 98.09it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 67%|βββββββ | 6/9 [00:00<00:00, 97.74it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 78%|ββββββββ | 7/9 [00:00<00:00, 98.53it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 78%|ββββββββ | 7/9 [00:00<00:00, 98.25it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 89%|βββββββββ | 8/9 [00:00<00:00, 98.60it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 89%|βββββββββ | 8/9 [00:00<00:00, 98.34it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.77it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.55it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.28it/s, v_num=Maps, val_loss=3.510, train_loss=0.611]
Epoch 24: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.73it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 24: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 11%|β | 1/9 [00:00<00:00, 94.74it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 11%|β | 1/9 [00:00<00:00, 92.70it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 22%|βββ | 2/9 [00:00<00:00, 97.63it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 22%|βββ | 2/9 [00:00<00:00, 96.57it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 33%|ββββ | 3/9 [00:00<00:00, 98.42it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 33%|ββββ | 3/9 [00:00<00:00, 97.70it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 44%|βββββ | 4/9 [00:00<00:00, 98.98it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 44%|βββββ | 4/9 [00:00<00:00, 98.49it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 56%|ββββββ | 5/9 [00:00<00:00, 98.78it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 56%|ββββββ | 5/9 [00:00<00:00, 98.34it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 67%|βββββββ | 6/9 [00:00<00:00, 98.98it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 67%|βββββββ | 6/9 [00:00<00:00, 98.61it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 78%|ββββββββ | 7/9 [00:00<00:00, 99.14it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 78%|ββββββββ | 7/9 [00:00<00:00, 98.82it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 89%|βββββββββ | 8/9 [00:00<00:00, 99.40it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 89%|βββββββββ | 8/9 [00:00<00:00, 99.12it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.89it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.65it/s, v_num=Maps, val_loss=3.510, train_loss=0.592]
Epoch 25: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.11it/s, v_num=Maps, val_loss=3.680, train_loss=0.592]
Epoch 25: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.56it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 25: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 11%|β | 1/9 [00:00<00:00, 95.26it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 11%|β | 1/9 [00:00<00:00, 93.39it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 22%|βββ | 2/9 [00:00<00:00, 97.14it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 22%|βββ | 2/9 [00:00<00:00, 96.17it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 33%|ββββ | 3/9 [00:00<00:00, 98.14it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 33%|ββββ | 3/9 [00:00<00:00, 97.48it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 44%|βββββ | 4/9 [00:00<00:00, 98.39it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 44%|βββββ | 4/9 [00:00<00:00, 97.90it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 56%|ββββββ | 5/9 [00:00<00:00, 98.97it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 56%|ββββββ | 5/9 [00:00<00:00, 98.57it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 67%|βββββββ | 6/9 [00:00<00:00, 99.46it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 67%|βββββββ | 6/9 [00:00<00:00, 99.12it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 78%|ββββββββ | 7/9 [00:00<00:00, 99.75it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 78%|ββββββββ | 7/9 [00:00<00:00, 99.43it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 89%|βββββββββ | 8/9 [00:00<00:00, 99.42it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 89%|βββββββββ | 8/9 [00:00<00:00, 99.16it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.51it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.29it/s, v_num=Maps, val_loss=3.680, train_loss=0.459]
Epoch 26: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.93it/s, v_num=Maps, val_loss=3.510, train_loss=0.459]
Epoch 26: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.37it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 26: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 11%|β | 1/9 [00:00<00:00, 95.77it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 11%|β | 1/9 [00:00<00:00, 93.86it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 22%|βββ | 2/9 [00:00<00:00, 97.67it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 22%|βββ | 2/9 [00:00<00:00, 96.69it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 33%|ββββ | 3/9 [00:00<00:00, 99.03it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 33%|ββββ | 3/9 [00:00<00:00, 98.30it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 44%|βββββ | 4/9 [00:00<00:00, 99.83it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 44%|βββββ | 4/9 [00:00<00:00, 99.33it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 56%|ββββββ | 5/9 [00:00<00:00, 99.68it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 56%|ββββββ | 5/9 [00:00<00:00, 99.28it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 67%|βββββββ | 6/9 [00:00<00:00, 100.09it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 67%|βββββββ | 6/9 [00:00<00:00, 99.75it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 78%|ββββββββ | 7/9 [00:00<00:00, 100.29it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 78%|ββββββββ | 7/9 [00:00<00:00, 100.00it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 89%|βββββββββ | 8/9 [00:00<00:00, 100.54it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 89%|βββββββββ | 8/9 [00:00<00:00, 100.28it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.33it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.10it/s, v_num=Maps, val_loss=3.510, train_loss=0.497]
Epoch 27: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.45it/s, v_num=Maps, val_loss=3.640, train_loss=0.497]
Epoch 27: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.89it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 27: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 11%|β | 1/9 [00:00<00:00, 86.83it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 11%|β | 1/9 [00:00<00:00, 84.97it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 22%|βββ | 2/9 [00:00<00:00, 90.18it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 22%|βββ | 2/9 [00:00<00:00, 89.25it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 33%|ββββ | 3/9 [00:00<00:00, 92.79it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 33%|ββββ | 3/9 [00:00<00:00, 92.17it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 44%|βββββ | 4/9 [00:00<00:00, 93.83it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 44%|βββββ | 4/9 [00:00<00:00, 93.37it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 56%|ββββββ | 5/9 [00:00<00:00, 93.60it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 56%|ββββββ | 5/9 [00:00<00:00, 93.24it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 67%|βββββββ | 6/9 [00:00<00:00, 94.58it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 67%|βββββββ | 6/9 [00:00<00:00, 94.27it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 78%|ββββββββ | 7/9 [00:00<00:00, 95.58it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 78%|ββββββββ | 7/9 [00:00<00:00, 95.31it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 89%|βββββββββ | 8/9 [00:00<00:00, 96.08it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 89%|βββββββββ | 8/9 [00:00<00:00, 95.84it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 100%|ββββββββββ| 9/9 [00:00<00:00, 97.38it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 100%|ββββββββββ| 9/9 [00:00<00:00, 97.17it/s, v_num=Maps, val_loss=3.640, train_loss=0.414]
Epoch 28: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.34it/s, v_num=Maps, val_loss=3.300, train_loss=0.414]
Epoch 28: 100%|ββββββββββ| 9/9 [00:00<00:00, 86.79it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 28: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 11%|β | 1/9 [00:00<00:00, 96.07it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 11%|β | 1/9 [00:00<00:00, 94.16it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 22%|βββ | 2/9 [00:00<00:00, 96.84it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 22%|βββ | 2/9 [00:00<00:00, 95.86it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 33%|ββββ | 3/9 [00:00<00:00, 97.07it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 33%|ββββ | 3/9 [00:00<00:00, 96.42it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 44%|βββββ | 4/9 [00:00<00:00, 96.90it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 44%|βββββ | 4/9 [00:00<00:00, 96.41it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 56%|ββββββ | 5/9 [00:00<00:00, 96.72it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 56%|ββββββ | 5/9 [00:00<00:00, 96.34it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 67%|βββββββ | 6/9 [00:00<00:00, 97.38it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 67%|βββββββ | 6/9 [00:00<00:00, 97.06it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 78%|ββββββββ | 7/9 [00:00<00:00, 97.93it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 78%|ββββββββ | 7/9 [00:00<00:00, 97.66it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 89%|βββββββββ | 8/9 [00:00<00:00, 98.40it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 89%|βββββββββ | 8/9 [00:00<00:00, 98.16it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.29it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.06it/s, v_num=Maps, val_loss=3.300, train_loss=0.382]
Epoch 29: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.96it/s, v_num=Maps, val_loss=3.350, train_loss=0.382]
Epoch 29: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.41it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 29: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 11%|β | 1/9 [00:00<00:00, 93.23it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 11%|β | 1/9 [00:00<00:00, 91.40it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 22%|βββ | 2/9 [00:00<00:00, 95.92it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 22%|βββ | 2/9 [00:00<00:00, 94.90it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 33%|ββββ | 3/9 [00:00<00:00, 97.59it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 33%|ββββ | 3/9 [00:00<00:00, 96.94it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 44%|βββββ | 4/9 [00:00<00:00, 98.14it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 44%|βββββ | 4/9 [00:00<00:00, 97.61it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 56%|ββββββ | 5/9 [00:00<00:00, 98.79it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 56%|ββββββ | 5/9 [00:00<00:00, 98.39it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 67%|βββββββ | 6/9 [00:00<00:00, 99.28it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 67%|βββββββ | 6/9 [00:00<00:00, 98.95it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 78%|ββββββββ | 7/9 [00:00<00:00, 99.77it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 78%|ββββββββ | 7/9 [00:00<00:00, 99.48it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 89%|βββββββββ | 8/9 [00:00<00:00, 99.59it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 89%|βββββββββ | 8/9 [00:00<00:00, 99.33it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.64it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.40it/s, v_num=Maps, val_loss=3.350, train_loss=0.501]
Epoch 30: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.83it/s, v_num=Maps, val_loss=3.290, train_loss=0.501]
Epoch 30: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.28it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 30: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 11%|β | 1/9 [00:00<00:00, 93.96it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 11%|β | 1/9 [00:00<00:00, 92.12it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 22%|βββ | 2/9 [00:00<00:00, 96.22it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 22%|βββ | 2/9 [00:00<00:00, 95.28it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 33%|ββββ | 3/9 [00:00<00:00, 98.04it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 33%|ββββ | 3/9 [00:00<00:00, 97.40it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 44%|βββββ | 4/9 [00:00<00:00, 99.02it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 44%|βββββ | 4/9 [00:00<00:00, 98.46it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 56%|ββββββ | 5/9 [00:00<00:00, 98.87it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 56%|ββββββ | 5/9 [00:00<00:00, 98.46it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 67%|βββββββ | 6/9 [00:00<00:00, 99.39it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 67%|βββββββ | 6/9 [00:00<00:00, 99.01it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 78%|ββββββββ | 7/9 [00:00<00:00, 99.63it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 78%|ββββββββ | 7/9 [00:00<00:00, 99.33it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 89%|βββββββββ | 8/9 [00:00<00:00, 99.58it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 89%|βββββββββ | 8/9 [00:00<00:00, 99.30it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.86it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.62it/s, v_num=Maps, val_loss=3.290, train_loss=0.438]
Epoch 31: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.30it/s, v_num=Maps, val_loss=3.350, train_loss=0.438]
Epoch 31: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.74it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 31: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 11%|β | 1/9 [00:00<00:00, 94.99it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 11%|β | 1/9 [00:00<00:00, 93.11it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 22%|βββ | 2/9 [00:00<00:00, 97.62it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 22%|βββ | 2/9 [00:00<00:00, 96.64it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 33%|ββββ | 3/9 [00:00<00:00, 98.44it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 33%|ββββ | 3/9 [00:00<00:00, 97.78it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 44%|βββββ | 4/9 [00:00<00:00, 98.43it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 44%|βββββ | 4/9 [00:00<00:00, 97.94it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 56%|ββββββ | 5/9 [00:00<00:00, 98.85it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 56%|ββββββ | 5/9 [00:00<00:00, 98.44it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 67%|βββββββ | 6/9 [00:00<00:00, 99.31it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 67%|βββββββ | 6/9 [00:00<00:00, 98.97it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 78%|ββββββββ | 7/9 [00:00<00:00, 99.63it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 78%|ββββββββ | 7/9 [00:00<00:00, 99.34it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 89%|βββββββββ | 8/9 [00:00<00:00, 99.48it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 89%|βββββββββ | 8/9 [00:00<00:00, 99.22it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.56it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.33it/s, v_num=Maps, val_loss=3.350, train_loss=0.451]
Epoch 32: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.87it/s, v_num=Maps, val_loss=3.290, train_loss=0.451]
Epoch 32: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.32it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 32: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 11%|β | 1/9 [00:00<00:00, 93.85it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 11%|β | 1/9 [00:00<00:00, 91.80it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 22%|βββ | 2/9 [00:00<00:00, 97.39it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 22%|βββ | 2/9 [00:00<00:00, 96.43it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 33%|ββββ | 3/9 [00:00<00:00, 97.92it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 33%|ββββ | 3/9 [00:00<00:00, 97.20it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 44%|βββββ | 4/9 [00:00<00:00, 98.75it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 44%|βββββ | 4/9 [00:00<00:00, 98.25it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 56%|ββββββ | 5/9 [00:00<00:00, 98.98it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 56%|ββββββ | 5/9 [00:00<00:00, 98.58it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 67%|βββββββ | 6/9 [00:00<00:00, 99.33it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 67%|βββββββ | 6/9 [00:00<00:00, 99.00it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 78%|ββββββββ | 7/9 [00:00<00:00, 99.65it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 78%|ββββββββ | 7/9 [00:00<00:00, 99.36it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 89%|βββββββββ | 8/9 [00:00<00:00, 99.98it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 89%|βββββββββ | 8/9 [00:00<00:00, 99.72it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.57it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.31it/s, v_num=Maps, val_loss=3.290, train_loss=0.455]
Epoch 33: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.91it/s, v_num=Maps, val_loss=3.280, train_loss=0.455]
Epoch 33: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.37it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 33: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 11%|β | 1/9 [00:00<00:00, 96.86it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 11%|β | 1/9 [00:00<00:00, 94.87it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 22%|βββ | 2/9 [00:00<00:00, 97.78it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 22%|βββ | 2/9 [00:00<00:00, 96.78it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 33%|ββββ | 3/9 [00:00<00:00, 98.57it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 33%|ββββ | 3/9 [00:00<00:00, 97.92it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 44%|βββββ | 4/9 [00:00<00:00, 98.86it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 44%|βββββ | 4/9 [00:00<00:00, 98.37it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 56%|ββββββ | 5/9 [00:00<00:00, 99.70it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 56%|ββββββ | 5/9 [00:00<00:00, 99.30it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 67%|βββββββ | 6/9 [00:00<00:00, 100.05it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 67%|βββββββ | 6/9 [00:00<00:00, 99.71it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 78%|ββββββββ | 7/9 [00:00<00:00, 100.43it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 78%|ββββββββ | 7/9 [00:00<00:00, 100.11it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 89%|βββββββββ | 8/9 [00:00<00:00, 100.34it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 89%|βββββββββ | 8/9 [00:00<00:00, 100.05it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.52it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.27it/s, v_num=Maps, val_loss=3.280, train_loss=0.458]
Epoch 34: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.45it/s, v_num=Maps, val_loss=3.370, train_loss=0.458]
Epoch 34: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.88it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 34: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 11%|β | 1/9 [00:00<00:00, 91.89it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 11%|β | 1/9 [00:00<00:00, 90.01it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 22%|βββ | 2/9 [00:00<00:00, 94.08it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 22%|βββ | 2/9 [00:00<00:00, 93.10it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 33%|ββββ | 3/9 [00:00<00:00, 95.16it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 33%|ββββ | 3/9 [00:00<00:00, 94.52it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 44%|βββββ | 4/9 [00:00<00:00, 95.90it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 44%|βββββ | 4/9 [00:00<00:00, 95.42it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 56%|ββββββ | 5/9 [00:00<00:00, 96.34it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 56%|ββββββ | 5/9 [00:00<00:00, 95.96it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 67%|βββββββ | 6/9 [00:00<00:00, 97.19it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 67%|βββββββ | 6/9 [00:00<00:00, 96.87it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 78%|ββββββββ | 7/9 [00:00<00:00, 97.78it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 78%|ββββββββ | 7/9 [00:00<00:00, 97.50it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 89%|βββββββββ | 8/9 [00:00<00:00, 97.53it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 89%|βββββββββ | 8/9 [00:00<00:00, 97.26it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.31it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.08it/s, v_num=Maps, val_loss=3.370, train_loss=0.496]
Epoch 35: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.91it/s, v_num=Maps, val_loss=3.140, train_loss=0.496]
Epoch 35: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.38it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 35: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 11%|β | 1/9 [00:00<00:00, 89.12it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 11%|β | 1/9 [00:00<00:00, 87.46it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 22%|βββ | 2/9 [00:00<00:00, 90.26it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 22%|βββ | 2/9 [00:00<00:00, 89.41it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 33%|ββββ | 3/9 [00:00<00:00, 92.45it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 33%|ββββ | 3/9 [00:00<00:00, 91.86it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 44%|βββββ | 4/9 [00:00<00:00, 93.20it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 44%|βββββ | 4/9 [00:00<00:00, 92.75it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 56%|ββββββ | 5/9 [00:00<00:00, 93.52it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 56%|ββββββ | 5/9 [00:00<00:00, 93.14it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 67%|βββββββ | 6/9 [00:00<00:00, 94.63it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 67%|βββββββ | 6/9 [00:00<00:00, 94.32it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 78%|ββββββββ | 7/9 [00:00<00:00, 95.11it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 78%|ββββββββ | 7/9 [00:00<00:00, 94.84it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 89%|βββββββββ | 8/9 [00:00<00:00, 95.10it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 89%|βββββββββ | 8/9 [00:00<00:00, 94.86it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 100%|ββββββββββ| 9/9 [00:00<00:00, 96.52it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 100%|ββββββββββ| 9/9 [00:00<00:00, 96.32it/s, v_num=Maps, val_loss=3.140, train_loss=0.396]
Epoch 36: 100%|ββββββββββ| 9/9 [00:00<00:00, 86.42it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 36: 100%|ββββββββββ| 9/9 [00:00<00:00, 85.91it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 36: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 11%|β | 1/9 [00:00<00:00, 88.00it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 11%|β | 1/9 [00:00<00:00, 86.13it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 22%|βββ | 2/9 [00:00<00:00, 91.55it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 22%|βββ | 2/9 [00:00<00:00, 90.65it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 33%|ββββ | 3/9 [00:00<00:00, 92.00it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 33%|ββββ | 3/9 [00:00<00:00, 91.31it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 44%|βββββ | 4/9 [00:00<00:00, 93.19it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 44%|βββββ | 4/9 [00:00<00:00, 92.69it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 56%|ββββββ | 5/9 [00:00<00:00, 92.85it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 56%|ββββββ | 5/9 [00:00<00:00, 92.47it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 67%|βββββββ | 6/9 [00:00<00:00, 93.42it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 67%|βββββββ | 6/9 [00:00<00:00, 93.10it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 78%|ββββββββ | 7/9 [00:00<00:00, 94.32it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 78%|ββββββββ | 7/9 [00:00<00:00, 94.05it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 89%|βββββββββ | 8/9 [00:00<00:00, 95.08it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 89%|βββββββββ | 8/9 [00:00<00:00, 94.85it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 100%|ββββββββββ| 9/9 [00:00<00:00, 96.21it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 100%|ββββββββββ| 9/9 [00:00<00:00, 95.98it/s, v_num=Maps, val_loss=3.310, train_loss=0.407]
Epoch 37: 100%|ββββββββββ| 9/9 [00:00<00:00, 86.26it/s, v_num=Maps, val_loss=3.340, train_loss=0.407]
Epoch 37: 100%|ββββββββββ| 9/9 [00:00<00:00, 85.74it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 37: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 11%|β | 1/9 [00:00<00:00, 96.65it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 11%|β | 1/9 [00:00<00:00, 94.72it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 22%|βββ | 2/9 [00:00<00:00, 98.46it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 22%|βββ | 2/9 [00:00<00:00, 97.47it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 33%|ββββ | 3/9 [00:00<00:00, 99.02it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 33%|ββββ | 3/9 [00:00<00:00, 98.35it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 44%|βββββ | 4/9 [00:00<00:00, 92.47it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 44%|βββββ | 4/9 [00:00<00:00, 91.84it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 56%|ββββββ | 5/9 [00:00<00:00, 92.59it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 56%|ββββββ | 5/9 [00:00<00:00, 92.23it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 67%|βββββββ | 6/9 [00:00<00:00, 94.21it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 67%|βββββββ | 6/9 [00:00<00:00, 93.88it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 78%|ββββββββ | 7/9 [00:00<00:00, 95.14it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 78%|ββββββββ | 7/9 [00:00<00:00, 94.88it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 89%|βββββββββ | 8/9 [00:00<00:00, 95.63it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 89%|βββββββββ | 8/9 [00:00<00:00, 95.36it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 100%|ββββββββββ| 9/9 [00:00<00:00, 97.03it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 100%|ββββββββββ| 9/9 [00:00<00:00, 96.79it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 100%|ββββββββββ| 9/9 [00:00<00:00, 86.83it/s, v_num=Maps, val_loss=3.340, train_loss=0.402]
Epoch 38: 100%|ββββββββββ| 9/9 [00:00<00:00, 86.29it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 38: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 11%|β | 1/9 [00:00<00:00, 83.78it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 11%|β | 1/9 [00:00<00:00, 81.94it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 22%|βββ | 2/9 [00:00<00:00, 89.28it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 22%|βββ | 2/9 [00:00<00:00, 88.42it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 33%|ββββ | 3/9 [00:00<00:00, 92.12it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 33%|ββββ | 3/9 [00:00<00:00, 91.53it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 44%|βββββ | 4/9 [00:00<00:00, 93.04it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 44%|βββββ | 4/9 [00:00<00:00, 92.55it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 56%|ββββββ | 5/9 [00:00<00:00, 94.01it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 56%|ββββββ | 5/9 [00:00<00:00, 93.64it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 67%|βββββββ | 6/9 [00:00<00:00, 94.51it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 67%|βββββββ | 6/9 [00:00<00:00, 94.17it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 78%|ββββββββ | 7/9 [00:00<00:00, 94.99it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 78%|ββββββββ | 7/9 [00:00<00:00, 94.73it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 89%|βββββββββ | 8/9 [00:00<00:00, 95.29it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 89%|βββββββββ | 8/9 [00:00<00:00, 95.03it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 100%|ββββββββββ| 9/9 [00:00<00:00, 96.34it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 100%|ββββββββββ| 9/9 [00:00<00:00, 96.13it/s, v_num=Maps, val_loss=3.340, train_loss=0.306]
Epoch 39: 100%|ββββββββββ| 9/9 [00:00<00:00, 86.26it/s, v_num=Maps, val_loss=3.210, train_loss=0.306]
Epoch 39: 100%|ββββββββββ| 9/9 [00:00<00:00, 85.75it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 39: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 11%|β | 1/9 [00:00<00:00, 88.65it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 11%|β | 1/9 [00:00<00:00, 86.90it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 22%|βββ | 2/9 [00:00<00:00, 91.74it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 22%|βββ | 2/9 [00:00<00:00, 90.84it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 33%|ββββ | 3/9 [00:00<00:00, 93.37it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 33%|ββββ | 3/9 [00:00<00:00, 92.72it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 44%|βββββ | 4/9 [00:00<00:00, 94.41it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 44%|βββββ | 4/9 [00:00<00:00, 93.96it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 56%|ββββββ | 5/9 [00:00<00:00, 95.73it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 56%|ββββββ | 5/9 [00:00<00:00, 95.36it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 67%|βββββββ | 6/9 [00:00<00:00, 96.45it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 67%|βββββββ | 6/9 [00:00<00:00, 96.14it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 78%|ββββββββ | 7/9 [00:00<00:00, 96.95it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 78%|ββββββββ | 7/9 [00:00<00:00, 96.67it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 89%|βββββββββ | 8/9 [00:00<00:00, 96.66it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 89%|βββββββββ | 8/9 [00:00<00:00, 96.41it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.15it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 100%|ββββββββββ| 9/9 [00:00<00:00, 97.92it/s, v_num=Maps, val_loss=3.210, train_loss=0.457]
Epoch 40: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.92it/s, v_num=Maps, val_loss=3.200, train_loss=0.457]
Epoch 40: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.40it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 40: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 11%|β | 1/9 [00:00<00:00, 96.84it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 11%|β | 1/9 [00:00<00:00, 94.87it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 22%|βββ | 2/9 [00:00<00:00, 98.88it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 22%|βββ | 2/9 [00:00<00:00, 97.74it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 33%|ββββ | 3/9 [00:00<00:00, 99.88it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 33%|ββββ | 3/9 [00:00<00:00, 99.21it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 44%|βββββ | 4/9 [00:00<00:00, 100.14it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 44%|βββββ | 4/9 [00:00<00:00, 99.63it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 56%|ββββββ | 5/9 [00:00<00:00, 100.13it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 56%|ββββββ | 5/9 [00:00<00:00, 99.72it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 67%|βββββββ | 6/9 [00:00<00:00, 100.59it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 67%|βββββββ | 6/9 [00:00<00:00, 100.25it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 78%|ββββββββ | 7/9 [00:00<00:00, 100.71it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 78%|ββββββββ | 7/9 [00:00<00:00, 100.41it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 89%|βββββββββ | 8/9 [00:00<00:00, 100.94it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 89%|βββββββββ | 8/9 [00:00<00:00, 100.65it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.55it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.31it/s, v_num=Maps, val_loss=3.200, train_loss=0.397]
Epoch 41: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.74it/s, v_num=Maps, val_loss=3.220, train_loss=0.397]
Epoch 41: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.17it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 41: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 11%|β | 1/9 [00:00<00:00, 97.91it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 11%|β | 1/9 [00:00<00:00, 95.78it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 22%|βββ | 2/9 [00:00<00:00, 99.45it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 22%|βββ | 2/9 [00:00<00:00, 98.43it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 33%|ββββ | 3/9 [00:00<00:00, 100.23it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 33%|ββββ | 3/9 [00:00<00:00, 99.51it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 44%|βββββ | 4/9 [00:00<00:00, 99.77it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 44%|βββββ | 4/9 [00:00<00:00, 99.26it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 56%|ββββββ | 5/9 [00:00<00:00, 100.12it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 56%|ββββββ | 5/9 [00:00<00:00, 99.69it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 67%|βββββββ | 6/9 [00:00<00:00, 99.86it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 67%|βββββββ | 6/9 [00:00<00:00, 99.52it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 78%|ββββββββ | 7/9 [00:00<00:00, 100.10it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 78%|ββββββββ | 7/9 [00:00<00:00, 99.80it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 89%|βββββββββ | 8/9 [00:00<00:00, 99.91it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 89%|βββββββββ | 8/9 [00:00<00:00, 99.64it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.00it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.77it/s, v_num=Maps, val_loss=3.220, train_loss=0.365]
Epoch 42: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.31it/s, v_num=Maps, val_loss=3.050, train_loss=0.365]
Epoch 42: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.75it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 42: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 11%|β | 1/9 [00:00<00:00, 95.82it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 11%|β | 1/9 [00:00<00:00, 93.92it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 22%|βββ | 2/9 [00:00<00:00, 97.93it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 22%|βββ | 2/9 [00:00<00:00, 96.95it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 33%|ββββ | 3/9 [00:00<00:00, 99.06it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 33%|ββββ | 3/9 [00:00<00:00, 98.39it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 44%|βββββ | 4/9 [00:00<00:00, 99.80it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 44%|βββββ | 4/9 [00:00<00:00, 99.29it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 56%|ββββββ | 5/9 [00:00<00:00, 99.62it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 56%|ββββββ | 5/9 [00:00<00:00, 99.22it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 67%|βββββββ | 6/9 [00:00<00:00, 100.26it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 67%|βββββββ | 6/9 [00:00<00:00, 99.92it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 78%|ββββββββ | 7/9 [00:00<00:00, 100.64it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 78%|ββββββββ | 7/9 [00:00<00:00, 100.30it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 89%|βββββββββ | 8/9 [00:00<00:00, 100.70it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 89%|βββββββββ | 8/9 [00:00<00:00, 100.45it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.34it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.11it/s, v_num=Maps, val_loss=3.050, train_loss=0.444]
Epoch 43: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.52it/s, v_num=Maps, val_loss=3.140, train_loss=0.444]
Epoch 43: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.95it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 43: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 11%|β | 1/9 [00:00<00:00, 96.18it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 11%|β | 1/9 [00:00<00:00, 94.28it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 22%|βββ | 2/9 [00:00<00:00, 98.60it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 22%|βββ | 2/9 [00:00<00:00, 97.51it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 33%|ββββ | 3/9 [00:00<00:00, 99.45it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 33%|ββββ | 3/9 [00:00<00:00, 98.68it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 44%|βββββ | 4/9 [00:00<00:00, 99.31it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 44%|βββββ | 4/9 [00:00<00:00, 98.76it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 56%|ββββββ | 5/9 [00:00<00:00, 99.84it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 56%|ββββββ | 5/9 [00:00<00:00, 99.40it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 67%|βββββββ | 6/9 [00:00<00:00, 100.42it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 67%|βββββββ | 6/9 [00:00<00:00, 100.08it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 78%|ββββββββ | 7/9 [00:00<00:00, 100.68it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 78%|ββββββββ | 7/9 [00:00<00:00, 100.38it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 89%|βββββββββ | 8/9 [00:00<00:00, 100.36it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 89%|βββββββββ | 8/9 [00:00<00:00, 100.09it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.52it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.28it/s, v_num=Maps, val_loss=3.140, train_loss=0.429]
Epoch 44: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.67it/s, v_num=Maps, val_loss=3.380, train_loss=0.429]
Epoch 44: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.10it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 44: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 11%|β | 1/9 [00:00<00:00, 87.10it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 11%|β | 1/9 [00:00<00:00, 85.49it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 22%|βββ | 2/9 [00:00<00:00, 92.06it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 22%|βββ | 2/9 [00:00<00:00, 91.19it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 33%|ββββ | 3/9 [00:00<00:00, 94.63it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 33%|ββββ | 3/9 [00:00<00:00, 94.02it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 44%|βββββ | 4/9 [00:00<00:00, 96.21it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 44%|βββββ | 4/9 [00:00<00:00, 95.74it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 56%|ββββββ | 5/9 [00:00<00:00, 96.82it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 56%|ββββββ | 5/9 [00:00<00:00, 96.44it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 67%|βββββββ | 6/9 [00:00<00:00, 97.61it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 67%|βββββββ | 6/9 [00:00<00:00, 97.29it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 78%|ββββββββ | 7/9 [00:00<00:00, 98.45it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 78%|ββββββββ | 7/9 [00:00<00:00, 98.16it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 89%|βββββββββ | 8/9 [00:00<00:00, 98.93it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 89%|βββββββββ | 8/9 [00:00<00:00, 98.66it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.88it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.65it/s, v_num=Maps, val_loss=3.380, train_loss=0.666]
Epoch 45: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.12it/s, v_num=Maps, val_loss=3.280, train_loss=0.666]
Epoch 45: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.55it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 45: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 11%|β | 1/9 [00:00<00:00, 89.66it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 11%|β | 1/9 [00:00<00:00, 87.71it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 22%|βββ | 2/9 [00:00<00:00, 93.49it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 22%|βββ | 2/9 [00:00<00:00, 92.58it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 33%|ββββ | 3/9 [00:00<00:00, 96.27it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 33%|ββββ | 3/9 [00:00<00:00, 95.57it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 44%|βββββ | 4/9 [00:00<00:00, 96.85it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 44%|βββββ | 4/9 [00:00<00:00, 96.37it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 56%|ββββββ | 5/9 [00:00<00:00, 97.93it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 56%|ββββββ | 5/9 [00:00<00:00, 97.54it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 67%|βββββββ | 6/9 [00:00<00:00, 98.49it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 67%|βββββββ | 6/9 [00:00<00:00, 98.15it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 78%|ββββββββ | 7/9 [00:00<00:00, 98.87it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 78%|ββββββββ | 7/9 [00:00<00:00, 98.58it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 89%|βββββββββ | 8/9 [00:00<00:00, 98.64it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 89%|βββββββββ | 8/9 [00:00<00:00, 98.35it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.89it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.64it/s, v_num=Maps, val_loss=3.280, train_loss=0.644]
Epoch 46: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.36it/s, v_num=Maps, val_loss=3.520, train_loss=0.644]
Epoch 46: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.80it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 46: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 11%|β | 1/9 [00:00<00:00, 97.35it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 11%|β | 1/9 [00:00<00:00, 95.20it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 22%|βββ | 2/9 [00:00<00:00, 98.44it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 22%|βββ | 2/9 [00:00<00:00, 97.31it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 33%|ββββ | 3/9 [00:00<00:00, 99.95it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 33%|ββββ | 3/9 [00:00<00:00, 99.28it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 44%|βββββ | 4/9 [00:00<00:00, 100.82it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 44%|βββββ | 4/9 [00:00<00:00, 100.31it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 56%|ββββββ | 5/9 [00:00<00:00, 100.65it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 56%|ββββββ | 5/9 [00:00<00:00, 100.24it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 67%|βββββββ | 6/9 [00:00<00:00, 101.18it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 67%|βββββββ | 6/9 [00:00<00:00, 100.80it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 78%|ββββββββ | 7/9 [00:00<00:00, 101.39it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 78%|ββββββββ | 7/9 [00:00<00:00, 101.09it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 89%|βββββββββ | 8/9 [00:00<00:00, 101.59it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 89%|βββββββββ | 8/9 [00:00<00:00, 101.33it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 100%|ββββββββββ| 9/9 [00:00<00:00, 102.19it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.94it/s, v_num=Maps, val_loss=3.520, train_loss=0.463]
Epoch 47: 100%|ββββββββββ| 9/9 [00:00<00:00, 91.18it/s, v_num=Maps, val_loss=3.310, train_loss=0.463]
Epoch 47: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.62it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 47: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 11%|β | 1/9 [00:00<00:00, 97.18it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 11%|β | 1/9 [00:00<00:00, 95.25it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 22%|βββ | 2/9 [00:00<00:00, 98.71it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 22%|βββ | 2/9 [00:00<00:00, 97.71it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 33%|ββββ | 3/9 [00:00<00:00, 99.57it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 33%|ββββ | 3/9 [00:00<00:00, 98.90it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 44%|βββββ | 4/9 [00:00<00:00, 99.24it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 44%|βββββ | 4/9 [00:00<00:00, 98.67it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 56%|ββββββ | 5/9 [00:00<00:00, 99.21it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 56%|ββββββ | 5/9 [00:00<00:00, 98.81it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 67%|βββββββ | 6/9 [00:00<00:00, 99.43it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 67%|βββββββ | 6/9 [00:00<00:00, 99.09it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 78%|ββββββββ | 7/9 [00:00<00:00, 99.68it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 78%|ββββββββ | 7/9 [00:00<00:00, 99.39it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 89%|βββββββββ | 8/9 [00:00<00:00, 99.57it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 89%|βββββββββ | 8/9 [00:00<00:00, 99.31it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.71it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.48it/s, v_num=Maps, val_loss=3.310, train_loss=0.396]
Epoch 48: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.02it/s, v_num=Maps, val_loss=3.270, train_loss=0.396]
Epoch 48: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.48it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 48: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 11%|β | 1/9 [00:00<00:00, 92.48it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 11%|β | 1/9 [00:00<00:00, 90.20it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 22%|βββ | 2/9 [00:00<00:00, 94.76it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 22%|βββ | 2/9 [00:00<00:00, 93.79it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 33%|ββββ | 3/9 [00:00<00:00, 96.28it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 33%|ββββ | 3/9 [00:00<00:00, 95.64it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 44%|βββββ | 4/9 [00:00<00:00, 97.56it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 44%|βββββ | 4/9 [00:00<00:00, 97.03it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 56%|ββββββ | 5/9 [00:00<00:00, 97.70it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 56%|ββββββ | 5/9 [00:00<00:00, 97.31it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 67%|βββββββ | 6/9 [00:00<00:00, 98.41it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 67%|βββββββ | 6/9 [00:00<00:00, 98.05it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 78%|ββββββββ | 7/9 [00:00<00:00, 98.94it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 78%|ββββββββ | 7/9 [00:00<00:00, 98.64it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 89%|βββββββββ | 8/9 [00:00<00:00, 99.38it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 89%|βββββββββ | 8/9 [00:00<00:00, 99.13it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.26it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.03it/s, v_num=Maps, val_loss=3.270, train_loss=0.425]
Epoch 49: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.57it/s, v_num=Maps, val_loss=3.200, train_loss=0.425]
Epoch 49: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.01it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 49: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 11%|β | 1/9 [00:00<00:00, 94.91it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 11%|β | 1/9 [00:00<00:00, 93.04it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 22%|βββ | 2/9 [00:00<00:00, 97.58it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 22%|βββ | 2/9 [00:00<00:00, 96.61it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 33%|ββββ | 3/9 [00:00<00:00, 98.79it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 33%|ββββ | 3/9 [00:00<00:00, 98.14it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 44%|βββββ | 4/9 [00:00<00:00, 99.05it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 44%|βββββ | 4/9 [00:00<00:00, 98.55it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 56%|ββββββ | 5/9 [00:00<00:00, 99.72it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 56%|ββββββ | 5/9 [00:00<00:00, 99.27it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 67%|βββββββ | 6/9 [00:00<00:00, 100.05it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 67%|βββββββ | 6/9 [00:00<00:00, 99.71it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 78%|ββββββββ | 7/9 [00:00<00:00, 100.25it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 78%|ββββββββ | 7/9 [00:00<00:00, 99.96it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 89%|βββββββββ | 8/9 [00:00<00:00, 100.26it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 89%|βββββββββ | 8/9 [00:00<00:00, 99.99it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.31it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 100%|ββββββββββ| 9/9 [00:00<00:00, 101.08it/s, v_num=Maps, val_loss=3.200, train_loss=0.433]
Epoch 50: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.57it/s, v_num=Maps, val_loss=3.150, train_loss=0.433]
Epoch 50: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.02it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 50: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 11%|β | 1/9 [00:00<00:00, 96.18it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 11%|β | 1/9 [00:00<00:00, 94.25it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 22%|βββ | 2/9 [00:00<00:00, 97.91it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 22%|βββ | 2/9 [00:00<00:00, 96.84it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 33%|ββββ | 3/9 [00:00<00:00, 99.08it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 33%|ββββ | 3/9 [00:00<00:00, 98.42it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 44%|βββββ | 4/9 [00:00<00:00, 99.82it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 44%|βββββ | 4/9 [00:00<00:00, 99.31it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 56%|ββββββ | 5/9 [00:00<00:00, 99.67it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 56%|ββββββ | 5/9 [00:00<00:00, 99.27it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 67%|βββββββ | 6/9 [00:00<00:00, 99.51it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 67%|βββββββ | 6/9 [00:00<00:00, 99.18it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 78%|ββββββββ | 7/9 [00:00<00:00, 99.73it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 78%|ββββββββ | 7/9 [00:00<00:00, 99.44it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 89%|βββββββββ | 8/9 [00:00<00:00, 100.09it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 89%|βββββββββ | 8/9 [00:00<00:00, 99.83it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.82it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.57it/s, v_num=Maps, val_loss=3.150, train_loss=0.330]
Epoch 51: 100%|ββββββββββ| 9/9 [00:00<00:00, 90.13it/s, v_num=Maps, val_loss=3.240, train_loss=0.330]
Epoch 51: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.59it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 51: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 11%|β | 1/9 [00:00<00:00, 97.58it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 11%|β | 1/9 [00:00<00:00, 95.63it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 22%|βββ | 2/9 [00:00<00:00, 98.99it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 22%|βββ | 2/9 [00:00<00:00, 97.99it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 33%|ββββ | 3/9 [00:00<00:00, 99.16it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 33%|ββββ | 3/9 [00:00<00:00, 98.49it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 44%|βββββ | 4/9 [00:00<00:00, 98.57it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 44%|βββββ | 4/9 [00:00<00:00, 98.07it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 56%|ββββββ | 5/9 [00:00<00:00, 98.91it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 56%|ββββββ | 5/9 [00:00<00:00, 98.51it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 67%|βββββββ | 6/9 [00:00<00:00, 99.42it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 67%|βββββββ | 6/9 [00:00<00:00, 99.08it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 78%|ββββββββ | 7/9 [00:00<00:00, 99.98it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 78%|ββββββββ | 7/9 [00:00<00:00, 99.66it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 89%|βββββββββ | 8/9 [00:00<00:00, 99.59it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 89%|βββββββββ | 8/9 [00:00<00:00, 99.33it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.46it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.23it/s, v_num=Maps, val_loss=3.240, train_loss=0.353]
Epoch 52: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.20it/s, v_num=Maps, val_loss=3.190, train_loss=0.353]
Epoch 52: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.62it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 52: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 11%|β | 1/9 [00:00<00:00, 93.81it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 11%|β | 1/9 [00:00<00:00, 92.00it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 22%|βββ | 2/9 [00:00<00:00, 96.78it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 22%|βββ | 2/9 [00:00<00:00, 95.81it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 33%|ββββ | 3/9 [00:00<00:00, 98.10it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 33%|ββββ | 3/9 [00:00<00:00, 97.15it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 44%|βββββ | 4/9 [00:00<00:00, 98.50it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 44%|βββββ | 4/9 [00:00<00:00, 98.00it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 56%|ββββββ | 5/9 [00:00<00:00, 98.14it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 56%|ββββββ | 5/9 [00:00<00:00, 97.72it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 67%|βββββββ | 6/9 [00:00<00:00, 98.66it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 67%|βββββββ | 6/9 [00:00<00:00, 98.33it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 78%|ββββββββ | 7/9 [00:00<00:00, 99.33it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 78%|ββββββββ | 7/9 [00:00<00:00, 99.04it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 89%|βββββββββ | 8/9 [00:00<00:00, 99.23it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 89%|βββββββββ | 8/9 [00:00<00:00, 98.98it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.04it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.80it/s, v_num=Maps, val_loss=3.190, train_loss=0.399]
Epoch 53: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.29it/s, v_num=Maps, val_loss=3.160, train_loss=0.399]
Epoch 53: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.72it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 53: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 11%|β | 1/9 [00:00<00:00, 92.10it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 11%|β | 1/9 [00:00<00:00, 90.13it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 22%|βββ | 2/9 [00:00<00:00, 94.99it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 22%|βββ | 2/9 [00:00<00:00, 93.96it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 33%|ββββ | 3/9 [00:00<00:00, 96.82it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 33%|ββββ | 3/9 [00:00<00:00, 96.11it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 44%|βββββ | 4/9 [00:00<00:00, 97.14it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 44%|βββββ | 4/9 [00:00<00:00, 96.66it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 56%|ββββββ | 5/9 [00:00<00:00, 98.16it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 56%|ββββββ | 5/9 [00:00<00:00, 97.73it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 67%|βββββββ | 6/9 [00:00<00:00, 98.68it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 67%|βββββββ | 6/9 [00:00<00:00, 98.35it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 78%|ββββββββ | 7/9 [00:00<00:00, 99.13it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 78%|ββββββββ | 7/9 [00:00<00:00, 98.84it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 89%|βββββββββ | 8/9 [00:00<00:00, 98.96it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 89%|βββββββββ | 8/9 [00:00<00:00, 98.70it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 100%|ββββββββββ| 9/9 [00:00<00:00, 100.16it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.90it/s, v_num=Maps, val_loss=3.160, train_loss=0.378]
Epoch 54: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.64it/s, v_num=Maps, val_loss=3.280, train_loss=0.378]
Epoch 54: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.09it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 54: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 11%|β | 1/9 [00:00<00:00, 92.91it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 11%|β | 1/9 [00:00<00:00, 91.10it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 22%|βββ | 2/9 [00:00<00:00, 96.06it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 22%|βββ | 2/9 [00:00<00:00, 95.11it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 33%|ββββ | 3/9 [00:00<00:00, 97.75it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 33%|ββββ | 3/9 [00:00<00:00, 97.10it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 44%|βββββ | 4/9 [00:00<00:00, 98.93it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 44%|βββββ | 4/9 [00:00<00:00, 98.43it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 56%|ββββββ | 5/9 [00:00<00:00, 98.91it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 56%|ββββββ | 5/9 [00:00<00:00, 98.51it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 67%|βββββββ | 6/9 [00:00<00:00, 99.60it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 67%|βββββββ | 6/9 [00:00<00:00, 99.23it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 78%|ββββββββ | 7/9 [00:00<00:00, 99.22it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 78%|ββββββββ | 7/9 [00:00<00:00, 98.93it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 89%|βββββββββ | 8/9 [00:00<00:00, 99.18it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 89%|βββββββββ | 8/9 [00:00<00:00, 98.93it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.67it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.41it/s, v_num=Maps, val_loss=3.280, train_loss=0.397]
Epoch 55: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.17it/s, v_num=Maps, val_loss=3.210, train_loss=0.397]
Epoch 55: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.60it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 55: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 11%|β | 1/9 [00:00<00:00, 93.67it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 11%|β | 1/9 [00:00<00:00, 91.73it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 22%|βββ | 2/9 [00:00<00:00, 94.88it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 22%|βββ | 2/9 [00:00<00:00, 93.95it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 33%|ββββ | 3/9 [00:00<00:00, 96.43it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 33%|ββββ | 3/9 [00:00<00:00, 95.78it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 44%|βββββ | 4/9 [00:00<00:00, 96.48it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 44%|βββββ | 4/9 [00:00<00:00, 95.95it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 56%|ββββββ | 5/9 [00:00<00:00, 97.19it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 56%|ββββββ | 5/9 [00:00<00:00, 96.72it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 67%|βββββββ | 6/9 [00:00<00:00, 97.24it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 67%|βββββββ | 6/9 [00:00<00:00, 96.91it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 78%|ββββββββ | 7/9 [00:00<00:00, 97.42it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 78%|ββββββββ | 7/9 [00:00<00:00, 97.13it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 89%|βββββββββ | 8/9 [00:00<00:00, 97.21it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 89%|βββββββββ | 8/9 [00:00<00:00, 96.96it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.31it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 100%|ββββββββββ| 9/9 [00:00<00:00, 98.07it/s, v_num=Maps, val_loss=3.210, train_loss=0.465]
Epoch 56: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.85it/s, v_num=Maps, val_loss=3.170, train_loss=0.465]
Epoch 56: 100%|ββββββββββ| 9/9 [00:00<00:00, 87.30it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 56: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 0%| | 0/9 [00:00<?, ?it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 11%|β | 1/9 [00:00<00:00, 94.07it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 11%|β | 1/9 [00:00<00:00, 92.17it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 22%|βββ | 2/9 [00:00<00:00, 96.90it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 22%|βββ | 2/9 [00:00<00:00, 95.92it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 33%|ββββ | 3/9 [00:00<00:00, 97.02it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 33%|ββββ | 3/9 [00:00<00:00, 96.37it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 44%|βββββ | 4/9 [00:00<00:00, 97.37it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 44%|βββββ | 4/9 [00:00<00:00, 96.88it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 56%|ββββββ | 5/9 [00:00<00:00, 97.20it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 56%|ββββββ | 5/9 [00:00<00:00, 96.77it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 67%|βββββββ | 6/9 [00:00<00:00, 97.79it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 67%|βββββββ | 6/9 [00:00<00:00, 97.43it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 78%|ββββββββ | 7/9 [00:00<00:00, 98.20it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 78%|ββββββββ | 7/9 [00:00<00:00, 97.93it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 89%|βββββββββ | 8/9 [00:00<00:00, 98.67it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 89%|βββββββββ | 8/9 [00:00<00:00, 98.42it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.53it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 100%|ββββββββββ| 9/9 [00:00<00:00, 99.27it/s, v_num=Maps, val_loss=3.170, train_loss=0.581]
Epoch 57: 100%|ββββββββββ| 9/9 [00:00<00:00, 89.08it/s, v_num=Maps, val_loss=3.190, train_loss=0.581]
Epoch 57: 100%|ββββββββββ| 9/9 [00:00<00:00, 88.50it/s, v_num=Maps, val_loss=3.190, train_loss=0.462]
Epoch 57: 100%|ββββββββββ| 9/9 [00:00<00:00, 74.22it/s, v_num=Maps, val_loss=3.190, train_loss=0.462]
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
Validate metric DataLoader 0
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
MAE_val 1.1853728294372559
R2_val 0.5987802743911743
val_loss 3.1867644786834717
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
Evaluating with validation dataο
Weβll start by evaluating the model with the validation data.
reals_preds_validation = RealsVsPreds.from_final_val_data(trained_model)
plt.show()
Evaluating with external dataο
Now weβll 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()
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 7.646 seconds)