Feat/add classification metrics#10
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…rom requirments.txt
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…1, pyg-library from requirments.txt
…1, pytorch-lightning==1.7.5 from requirments.txt
…1, pytorch-lightning==1.7.5 from requirments.txt
…1, pytorch-lightning==1.7.5, scikit-learn==1.2.0 from requirments.txt
…1, pytorch-lightning==1.7.5, scikit-learn==1.2.0 from requirments.txt
…1, pytorch-lightning==1.7.5, scikit-learn==1.2.0, scipy==1.10.0 from requirments.txt
…1, pytorch-lightning==1.7.5, scikit-learn==1.2.0, scipy==1.10.0 from requirments.txt
…1, pytorch-lightning==1.7.5, scikit-learn==1.2.0, scipy==1.10.0 from requirments.txt
…1, pytorch-lightning==1.7.5, scikit-learn==1.2.0, scipy==1.10.0 from requirments.txt
…1, pytorch-lightning==1.7.5, scikit-learn==1.2.0, scipy==1.10.0 from requirments.txt
…1, pytorch-lightning==1.7.5, scikit-learn==1.2.0, scipy==1.10.0 from requirments.txt
…1, pytorch-lightning==1.7.5, scikit-learn==1.2.0, scipy==1.10.0 from requirments.txt
…1, pytorch-lightning==1.7.5, scikit-learn==1.2.0, scipy==1.10.0 from requirments.txt
…1, pytorch-lightning==1.7.5, scikit-learn==1.2.0, scipy==1.10.0 from requirments.txt
…1, pytorch-lightning==1.7.5, scikit-learn==1.2.0, scipy==1.10.0 from requirments.txt
This commit enhances the training process by calculating and displaying F1-score, recall, and precision in addition to accuracy and loss. Changes include: - Modified the `do_epoch` method in `ge/Models/trainer.py` to compute F1-score, recall, and precision. These metrics are calculated across the entire epoch's predictions and true labels for better accuracy, using `sklearn.metrics` with 'weighted' averaging and `zero_division=0`. - Updated the `epoch_metrics` dictionary to include these new metrics. - Modified the print statement within the `train_and_eval` method in `ge/Models/trainer.py` to log these new metrics for both training and validation phases when `train_log` is enabled.
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