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End of training

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README.md CHANGED
@@ -9,23 +9,23 @@ metrics:
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  - recall
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  - f1
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  model-index:
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- - name: 080524_epoch_1
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # 080524_epoch_1
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  This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cased-te](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cased-te) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8412
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- - Accuracy: 0.6261
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- - Precision: 0.6471
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- - Recall: 0.6261
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- - F1: 0.6122
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- - Ratio: 0.6891
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  ## Model description
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@@ -61,12 +61,12 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Ratio |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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- | 3.4777 | 0.1626 | 10 | 1.9887 | 0.5336 | 0.5436 | 0.5336 | 0.5052 | 0.7395 |
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- | 1.6106 | 0.3252 | 20 | 1.2180 | 0.5504 | 0.5532 | 0.5504 | 0.5446 | 0.3866 |
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- | 0.9895 | 0.4878 | 30 | 0.9875 | 0.5672 | 0.5736 | 0.5672 | 0.5577 | 0.6471 |
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- | 0.9363 | 0.6504 | 40 | 0.8740 | 0.6176 | 0.6183 | 0.6176 | 0.6171 | 0.4622 |
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- | 0.8844 | 0.8130 | 50 | 0.8591 | 0.6134 | 0.6378 | 0.6134 | 0.5956 | 0.7101 |
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- | 0.8565 | 0.9756 | 60 | 0.8416 | 0.6218 | 0.6433 | 0.6218 | 0.6072 | 0.6933 |
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  ### Framework versions
 
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  - recall
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  - f1
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  model-index:
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+ - name: 080524_epoch_2
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ # 080524_epoch_2
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  This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cased-te](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cased-te) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6633
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+ - Accuracy: 0.7941
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+ - Precision: 0.8018
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+ - Recall: 0.7941
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+ - F1: 0.7928
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+ - Ratio: 0.5798
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Ratio |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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+ | 0.8337 | 0.1626 | 10 | 0.7759 | 0.7101 | 0.7126 | 0.7101 | 0.7092 | 0.4454 |
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+ | 0.7644 | 0.3252 | 20 | 0.7252 | 0.7563 | 0.7654 | 0.7563 | 0.7542 | 0.5924 |
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+ | 0.7339 | 0.4878 | 30 | 0.6925 | 0.7689 | 0.7732 | 0.7689 | 0.7680 | 0.5630 |
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+ | 0.7102 | 0.6504 | 40 | 0.6907 | 0.7647 | 0.7802 | 0.7647 | 0.7614 | 0.6176 |
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+ | 0.7758 | 0.8130 | 50 | 0.6682 | 0.7857 | 0.7917 | 0.7857 | 0.7846 | 0.5714 |
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+ | 0.6621 | 0.9756 | 60 | 0.6632 | 0.7899 | 0.7967 | 0.7899 | 0.7887 | 0.5756 |
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  ### Framework versions
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