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lBober/my-model-Bertin-Sentimento

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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 [bertin-project/bertin-roberta-base-spanish](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2367
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- - Accuracy: 0.9355
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- - F1: 0.9386
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- - Precision: 0.9439
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- - Recall: 0.9355
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  ## Model description
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@@ -43,9 +43,9 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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- - train_batch_size: 20
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- - eval_batch_size: 20
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 0.4974 | 1.0 | 37 | 0.2835 | 0.8968 | 0.8480 | 0.8042 | 0.8968 |
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- | 0.288 | 2.0 | 74 | 0.2301 | 0.9161 | 0.9193 | 0.9236 | 0.9161 |
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- | 0.1452 | 3.0 | 111 | 0.2097 | 0.9290 | 0.9280 | 0.9272 | 0.9290 |
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- | 0.0708 | 4.0 | 148 | 0.1820 | 0.9419 | 0.9392 | 0.9383 | 0.9419 |
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- | 0.0249 | 5.0 | 185 | 0.2367 | 0.9355 | 0.9386 | 0.9439 | 0.9355 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bertin-project/bertin-roberta-base-spanish](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2655
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+ - Accuracy: 0.9419
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+ - F1: 0.7805
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+ - Precision: 0.8889
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+ - Recall: 0.6957
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.3854 | 1.0 | 91 | 0.2982 | 0.9097 | 0.6111 | 0.8462 | 0.4783 |
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+ | 0.2292 | 2.0 | 182 | 0.5019 | 0.8968 | 0.5 | 0.8889 | 0.3478 |
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+ | 0.113 | 3.0 | 273 | 0.3843 | 0.9290 | 0.7556 | 0.7727 | 0.7391 |
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+ | 0.051 | 4.0 | 364 | 0.3038 | 0.9355 | 0.8077 | 0.7241 | 0.9130 |
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+ | 0.0267 | 5.0 | 455 | 0.2655 | 0.9419 | 0.7805 | 0.8889 | 0.6957 |
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  ### Framework versions
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