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my-model-SaBERT-Sentimento

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lBober/my-model-Sabert-Sentimento

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  1. README.md +11 -11
  2. model.safetensors +1 -1
  3. runs/May25_15-57-37_fe998d142f54/events.out.tfevents.1716652657.fe998d142f54.14036.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -9,21 +9,21 @@ metrics:
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  - precision
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  - recall
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  model-index:
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- - name: my-model-SaBERT-Sentimento
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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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- # my-model-SaBERT-Sentimento
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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: 0.2866
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  - Accuracy: 0.9355
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- - F1: 0.9362
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- - Precision: 0.9403
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  - Recall: 0.9355
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  ## Model description
@@ -43,7 +43,7 @@ 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
@@ -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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- | 0.3225 | 1.0 | 37 | 0.2158 | 0.9355 | 0.9348 | 0.9355 | 0.9355 |
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- | 0.1283 | 2.0 | 74 | 0.2217 | 0.9484 | 0.9472 | 0.9473 | 0.9484 |
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- | 0.0753 | 3.0 | 111 | 0.2598 | 0.9355 | 0.9362 | 0.9403 | 0.9355 |
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- | 0.0503 | 4.0 | 148 | 0.2878 | 0.9290 | 0.9309 | 0.9373 | 0.9290 |
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- | 0.0397 | 5.0 | 185 | 0.2866 | 0.9355 | 0.9362 | 0.9403 | 0.9355 |
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  ### Framework versions
 
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  - precision
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  - recall
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  model-index:
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+ - name: my-model-Sabert-Sentimento
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  results: []
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  ---
15
 
16
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
17
  should probably proofread and complete it, then remove this comment. -->
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+ # my-model-Sabert-Sentimento
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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: 0.2475
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  - Accuracy: 0.9355
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+ - F1: 0.9244
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+ - Precision: 0.9204
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  - Recall: 0.9355
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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: 2e-06
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.8062 | 1.0 | 37 | 0.5185 | 0.9419 | 0.9248 | 0.9389 | 0.9419 |
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+ | 0.4799 | 2.0 | 74 | 0.3278 | 0.9419 | 0.9248 | 0.9389 | 0.9419 |
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+ | 0.3556 | 3.0 | 111 | 0.2730 | 0.9355 | 0.9244 | 0.9204 | 0.9355 |
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+ | 0.3058 | 4.0 | 148 | 0.2532 | 0.9355 | 0.9244 | 0.9204 | 0.9355 |
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+ | 0.2785 | 5.0 | 185 | 0.2475 | 0.9355 | 0.9244 | 0.9204 | 0.9355 |
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  ### Framework versions
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