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my-model-SaBERT-Sentimento

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lBober/my-model-Sabert-Sentimento

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  1. README.md +13 -13
  2. model.safetensors +1 -1
  3. runs/May25_16-36-27_fe998d142f54/events.out.tfevents.1716654988.fe998d142f54.25939.0 +3 -0
  4. training_args.bin +1 -1
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 [VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis](https://huggingface.co/VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3596
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- - Accuracy: 0.9161
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- - F1: 0.9167
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- - Precision: 0.9193
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- - Recall: 0.9161
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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: 3e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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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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- | 0.2944 | 1.0 | 46 | 0.2173 | 0.9226 | 0.9204 | 0.9184 | 0.9226 |
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- | 0.1038 | 2.0 | 92 | 0.2623 | 0.9355 | 0.9331 | 0.9309 | 0.9355 |
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- | 0.0589 | 3.0 | 138 | 0.4238 | 0.9161 | 0.9196 | 0.9301 | 0.9161 |
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- | 0.0354 | 4.0 | 184 | 0.3488 | 0.9161 | 0.9167 | 0.9193 | 0.9161 |
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- | 0.0225 | 5.0 | 230 | 0.3596 | 0.9161 | 0.9167 | 0.9193 | 0.9161 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis](https://huggingface.co/VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3684
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+ - Accuracy: 0.8839
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+ - F1: 0.8294
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+ - Precision: 0.7812
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+ - Recall: 0.8839
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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: 0.003
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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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+ | 1.0041 | 1.0 | 37 | 0.4475 | 0.8839 | 0.8294 | 0.7812 | 0.8839 |
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+ | 0.4618 | 2.0 | 74 | 0.4023 | 0.8839 | 0.8294 | 0.7812 | 0.8839 |
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+ | 0.4878 | 3.0 | 111 | 0.3611 | 0.8839 | 0.8294 | 0.7812 | 0.8839 |
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+ | 0.4053 | 4.0 | 148 | 0.3654 | 0.8839 | 0.8294 | 0.7812 | 0.8839 |
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+ | 0.4072 | 5.0 | 185 | 0.3684 | 0.8839 | 0.8294 | 0.7812 | 0.8839 |
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  ### Framework versions
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