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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_3
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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_3
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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: 0.7190
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- - Accuracy: 0.8151
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- - Precision: 0.8431
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- - Recall: 0.8151
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- - F1: 0.8113
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- - Ratio: 0.6429
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  ## Model description
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@@ -61,14 +61,14 @@ 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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- | 0.4532 | 0.1176 | 10 | 0.6742 | 0.8193 | 0.8367 | 0.8193 | 0.8170 | 0.6134 |
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- | 0.4299 | 0.2353 | 20 | 0.8276 | 0.7731 | 0.8079 | 0.7731 | 0.7665 | 0.6681 |
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- | 0.4963 | 0.3529 | 30 | 0.7032 | 0.8235 | 0.8425 | 0.8235 | 0.8211 | 0.6176 |
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- | 0.3726 | 0.4706 | 40 | 0.7220 | 0.8193 | 0.8395 | 0.8193 | 0.8166 | 0.6218 |
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- | 0.3917 | 0.5882 | 50 | 0.8389 | 0.7941 | 0.8295 | 0.7941 | 0.7884 | 0.6639 |
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- | 0.4565 | 0.7059 | 60 | 0.7085 | 0.8277 | 0.8429 | 0.8277 | 0.8258 | 0.6050 |
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- | 0.4748 | 0.8235 | 70 | 0.6934 | 0.8109 | 0.8278 | 0.8109 | 0.8085 | 0.6134 |
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- | 0.4813 | 0.9412 | 80 | 0.7157 | 0.8193 | 0.8426 | 0.8193 | 0.8162 | 0.6303 |
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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_5
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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_5
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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: 0.7216
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+ - Accuracy: 0.8487
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+ - Precision: 0.8635
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+ - Recall: 0.8487
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+ - F1: 0.8472
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+ - Ratio: 0.6008
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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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+ | 0.3218 | 0.1176 | 10 | 0.8879 | 0.7899 | 0.8408 | 0.7899 | 0.7818 | 0.6933 |
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+ | 0.3938 | 0.2353 | 20 | 0.7170 | 0.8277 | 0.8306 | 0.8277 | 0.8274 | 0.5462 |
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+ | 0.3888 | 0.3529 | 30 | 0.7764 | 0.8151 | 0.8397 | 0.8151 | 0.8117 | 0.6345 |
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+ | 0.3461 | 0.4706 | 40 | 0.8152 | 0.8025 | 0.8349 | 0.8025 | 0.7976 | 0.6555 |
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+ | 0.3383 | 0.5882 | 50 | 0.7501 | 0.8361 | 0.8469 | 0.8361 | 0.8348 | 0.5882 |
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+ | 0.3509 | 0.7059 | 60 | 0.7500 | 0.8403 | 0.8574 | 0.8403 | 0.8384 | 0.6092 |
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+ | 0.3862 | 0.8235 | 70 | 0.7365 | 0.8487 | 0.8635 | 0.8487 | 0.8472 | 0.6008 |
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+ | 0.435 | 0.9412 | 80 | 0.7224 | 0.8487 | 0.8635 | 0.8487 | 0.8472 | 0.6008 |
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  ### Framework versions
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