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End of training

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README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [manucos/final-ft__roberta-base-biomedical-clinical-es__70k-ultrasounds](https://huggingface.co/manucos/final-ft__roberta-base-biomedical-clinical-es__70k-ultrasounds) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3564
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- - Precision: 0.8743
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- - Recall: 0.8963
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- - F1: 0.8851
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- - Accuracy: 0.9405
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  ## Model description
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@@ -55,21 +55,21 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 280 | 0.2918 | 0.8036 | 0.8548 | 0.8284 | 0.9271 |
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- | 0.3032 | 2.0 | 560 | 0.2601 | 0.8136 | 0.8859 | 0.8482 | 0.9346 |
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- | 0.3032 | 3.0 | 840 | 0.2412 | 0.8573 | 0.8815 | 0.8692 | 0.9366 |
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- | 0.1275 | 4.0 | 1120 | 0.2480 | 0.8487 | 0.8978 | 0.8726 | 0.9425 |
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- | 0.1275 | 5.0 | 1400 | 0.2934 | 0.8457 | 0.8933 | 0.8689 | 0.9335 |
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- | 0.0739 | 6.0 | 1680 | 0.2979 | 0.8660 | 0.9096 | 0.8873 | 0.9408 |
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- | 0.0739 | 7.0 | 1960 | 0.3159 | 0.8651 | 0.8933 | 0.8790 | 0.9338 |
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- | 0.042 | 8.0 | 2240 | 0.3255 | 0.8669 | 0.8874 | 0.8770 | 0.9374 |
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- | 0.0308 | 9.0 | 2520 | 0.3467 | 0.8541 | 0.8933 | 0.8733 | 0.9391 |
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- | 0.0308 | 10.0 | 2800 | 0.3228 | 0.8651 | 0.8933 | 0.8790 | 0.9383 |
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- | 0.024 | 11.0 | 3080 | 0.3498 | 0.8699 | 0.8919 | 0.8808 | 0.9346 |
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- | 0.024 | 12.0 | 3360 | 0.3465 | 0.8792 | 0.8948 | 0.8869 | 0.9419 |
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- | 0.019 | 13.0 | 3640 | 0.3596 | 0.8705 | 0.8963 | 0.8832 | 0.9363 |
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- | 0.019 | 14.0 | 3920 | 0.3557 | 0.8693 | 0.8963 | 0.8826 | 0.9386 |
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- | 0.0157 | 15.0 | 4200 | 0.3564 | 0.8743 | 0.8963 | 0.8851 | 0.9405 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [manucos/final-ft__roberta-base-biomedical-clinical-es__70k-ultrasounds](https://huggingface.co/manucos/final-ft__roberta-base-biomedical-clinical-es__70k-ultrasounds) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3148
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+ - Precision: 0.8725
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+ - Recall: 0.9022
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+ - F1: 0.8871
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+ - Accuracy: 0.9419
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 280 | 0.3056 | 0.7819 | 0.8444 | 0.8120 | 0.9198 |
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+ | 0.4846 | 2.0 | 560 | 0.2545 | 0.8126 | 0.88 | 0.8450 | 0.9360 |
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+ | 0.4846 | 3.0 | 840 | 0.2269 | 0.8671 | 0.8889 | 0.8778 | 0.9414 |
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+ | 0.1366 | 4.0 | 1120 | 0.2519 | 0.8225 | 0.8993 | 0.8592 | 0.9372 |
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+ | 0.1366 | 5.0 | 1400 | 0.2449 | 0.8472 | 0.9037 | 0.8746 | 0.9445 |
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+ | 0.0788 | 6.0 | 1680 | 0.2839 | 0.8725 | 0.9022 | 0.8871 | 0.9419 |
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+ | 0.0788 | 7.0 | 1960 | 0.2849 | 0.8631 | 0.8963 | 0.8794 | 0.9386 |
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+ | 0.0441 | 8.0 | 2240 | 0.2987 | 0.8736 | 0.9007 | 0.8869 | 0.9397 |
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+ | 0.0335 | 9.0 | 2520 | 0.3192 | 0.8602 | 0.9022 | 0.8807 | 0.9377 |
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+ | 0.0335 | 10.0 | 2800 | 0.3094 | 0.8734 | 0.8993 | 0.8861 | 0.9414 |
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+ | 0.0242 | 11.0 | 3080 | 0.3233 | 0.8748 | 0.9007 | 0.8876 | 0.9383 |
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+ | 0.0242 | 12.0 | 3360 | 0.3215 | 0.8764 | 0.9037 | 0.8899 | 0.9417 |
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+ | 0.0189 | 13.0 | 3640 | 0.3155 | 0.8684 | 0.8993 | 0.8836 | 0.9405 |
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+ | 0.0189 | 14.0 | 3920 | 0.3156 | 0.8725 | 0.9022 | 0.8871 | 0.9425 |
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+ | 0.0172 | 15.0 | 4200 | 0.3148 | 0.8725 | 0.9022 | 0.8871 | 0.9419 |
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  ### Framework versions
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