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my-model-SaBERT-Sentimento

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lBober/my-model-SaBERT-Sentimento

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  1. README.md +10 -10
  2. model.safetensors +1 -1
  3. runs/May26_09-24-06_6b3393198f09/events.out.tfevents.1716715447.6b3393198f09.5457.0 +3 -0
  4. runs/May26_09-26-01_6b3393198f09/events.out.tfevents.1716715561.6b3393198f09.7041.0 +3 -0
  5. runs/May26_09-28-04_6b3393198f09/events.out.tfevents.1716715685.6b3393198f09.7720.0 +3 -0
  6. runs/May26_09-33-43_6b3393198f09/events.out.tfevents.1716716024.6b3393198f09.9473.0 +3 -0
  7. runs/May26_09-33-43_6b3393198f09/events.out.tfevents.1716716123.6b3393198f09.9473.1 +3 -0
  8. 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: 0.6195
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- - Accuracy: 0.9097
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- - F1: 0.6316
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- - Precision: 0.8
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- - Recall: 0.5217
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  ## Model description
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@@ -55,11 +55,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 0.3203 | 1.0 | 91 | 0.4086 | 0.9032 | 0.5946 | 0.7857 | 0.4783 |
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- | 0.1896 | 2.0 | 182 | 0.3912 | 0.9032 | 0.5714 | 0.8333 | 0.4348 |
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- | 0.0667 | 3.0 | 273 | 0.6001 | 0.9032 | 0.5714 | 0.8333 | 0.4348 |
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- | 0.028 | 4.0 | 364 | 0.6256 | 0.8968 | 0.5556 | 0.7692 | 0.4348 |
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- | 0.0098 | 5.0 | 455 | 0.6195 | 0.9097 | 0.6316 | 0.8 | 0.5217 |
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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: 0.2778
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+ - Accuracy: 0.9548
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+ - F1: 0.9491
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+ - Precision: 0.9482
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+ - Recall: 0.9548
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.3001 | 1.0 | 91 | 0.1484 | 0.9355 | 0.9279 | 0.9268 | 0.9355 |
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+ | 0.1476 | 2.0 | 182 | 0.1431 | 0.9419 | 0.9370 | 0.9336 | 0.9419 |
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+ | 0.0432 | 3.0 | 273 | 0.2762 | 0.9419 | 0.9382 | 0.9347 | 0.9419 |
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+ | 0.0173 | 4.0 | 364 | 0.2632 | 0.9419 | 0.9370 | 0.9336 | 0.9419 |
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+ | 0.0075 | 5.0 | 455 | 0.2778 | 0.9548 | 0.9491 | 0.9482 | 0.9548 |
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  ### Framework versions
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