Commit
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Parent(s):
0d9fb25
End of training
Browse files
README.md
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This model was trained from scratch on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Comment: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number':
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- Date: {'precision': 0.
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- Labname: {'precision': 0.
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- Laboratory: {'precision': 0.
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- Measure: {'precision': 0.
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- Overall
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- Overall
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- Overall
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- Overall Accuracy: 0.4200
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Comment | Date
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### Framework versions
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This model was trained from scratch on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4919
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- Comment: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6}
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- Date: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
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- Labname: {'precision': 0.5833333333333334, 'recall': 0.6666666666666666, 'f1': 0.6222222222222222, 'number': 21}
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- Laboratory: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
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- Measure: {'precision': 0.5833333333333334, 'recall': 0.7777777777777778, 'f1': 0.6666666666666666, 'number': 9}
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- Ref Value: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8}
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- Result: {'precision': 0.25, 'recall': 0.25, 'f1': 0.25, 'number': 12}
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- Overall Precision: 0.4528
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- Overall Recall: 0.4
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- Overall F1: 0.4248
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- Overall Accuracy: 0.8698
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Comment | Date | Labname | Laboratory | Measure | Ref Value | Result | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------:|:------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------:|:------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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| 2.4398 | 5.0 | 5 | 1.5928 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 12} | 0.0 | 0.0 | 0.0 | 0.5850 |
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| 1.4788 | 10.0 | 10 | 1.1857 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 12} | 0.0 | 0.0 | 0.0 | 0.6512 |
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| 0.9806 | 15.0 | 15 | 0.8188 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.21875, 'recall': 0.3333333333333333, 'f1': 0.2641509433962264, 'number': 21} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.5, 'recall': 0.1111111111111111, 'f1': 0.1818181818181818, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 12} | 0.1667 | 0.1333 | 0.1481 | 0.7660 |
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| 0.6358 | 20.0 | 20 | 0.5763 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.41935483870967744, 'recall': 0.6190476190476191, 'f1': 0.5, 'number': 21} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.7, 'recall': 0.7777777777777778, 'f1': 0.7368421052631577, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8} | {'precision': 0.42857142857142855, 'recall': 0.25, 'f1': 0.3157894736842105, 'number': 12} | 0.4182 | 0.3833 | 0.4 | 0.8675 |
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| 0.4712 | 25.0 | 25 | 0.4919 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.5833333333333334, 'recall': 0.6666666666666666, 'f1': 0.6222222222222222, 'number': 21} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.5833333333333334, 'recall': 0.7777777777777778, 'f1': 0.6666666666666666, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8} | {'precision': 0.25, 'recall': 0.25, 'f1': 0.25, 'number': 12} | 0.4528 | 0.4 | 0.4248 | 0.8698 |
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### Framework versions
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logs/events.out.tfevents.1674460236.pc092u.2809614.0
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logs/events.out.tfevents.1674460272.pc092u.2809614.2
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