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README.md CHANGED
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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: 0.6204
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- - Accuracy: 0.8369
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- - Precision: 0.8404
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- - Recall: 0.8369
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- - F1: 0.8365
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- - Ratio: 0.5503
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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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- | 0.5486 | 0.1626 | 10 | 0.6592 | 0.8282 | 0.8355 | 0.8282 | 0.8272 | 0.4262 |
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- | 0.553 | 0.3252 | 20 | 0.6085 | 0.8309 | 0.8311 | 0.8309 | 0.8308 | 0.5134 |
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- | 0.4779 | 0.4878 | 30 | 0.6103 | 0.8349 | 0.8416 | 0.8349 | 0.8341 | 0.4302 |
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- | 0.4642 | 0.6504 | 40 | 0.6080 | 0.8356 | 0.8356 | 0.8356 | 0.8356 | 0.4926 |
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- | 0.4546 | 0.8130 | 50 | 0.6739 | 0.8161 | 0.8291 | 0.8161 | 0.8143 | 0.5993 |
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- | 0.5207 | 0.9756 | 60 | 0.6204 | 0.8369 | 0.8404 | 0.8369 | 0.8365 | 0.5503 |
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  ### Framework versions
 
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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: 0.6453
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+ - Accuracy: 0.8309
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+ - Precision: 0.8362
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+ - Recall: 0.8309
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+ - F1: 0.8302
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+ - Ratio: 0.5631
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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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+ | 0.5106 | 0.1626 | 10 | 0.6599 | 0.8289 | 0.8500 | 0.8289 | 0.8262 | 0.3772 |
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+ | 0.5228 | 0.3252 | 20 | 0.5642 | 0.8517 | 0.8517 | 0.8517 | 0.8517 | 0.5020 |
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+ | 0.5035 | 0.4878 | 30 | 0.5669 | 0.8544 | 0.8554 | 0.8544 | 0.8543 | 0.4725 |
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+ | 0.4325 | 0.6504 | 40 | 0.6077 | 0.8403 | 0.8442 | 0.8403 | 0.8398 | 0.4463 |
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+ | 0.4902 | 0.8130 | 50 | 0.6391 | 0.8322 | 0.8369 | 0.8322 | 0.8316 | 0.5591 |
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+ | 0.4774 | 0.9756 | 60 | 0.6453 | 0.8309 | 0.8362 | 0.8309 | 0.8302 | 0.5631 |
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  ### Framework versions
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