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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_16-17-32_fe998d142f54/events.out.tfevents.1716653853.fe998d142f54.20147.0 +3 -0
  4. runs/May25_16-19-40_fe998d142f54/events.out.tfevents.1716653981.fe998d142f54.20871.0 +3 -0
  5. 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: 0.2958
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- - Accuracy: 0.9226
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- - F1: 0.9157
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- - Precision: 0.9091
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- - Recall: 0.9226
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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-05
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  - train_batch_size: 50
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  - eval_batch_size: 50
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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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- | 0.4886 | 1.0 | 15 | 0.2474 | 0.9226 | 0.9123 | 0.9066 | 0.9226 |
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- | 0.1469 | 2.0 | 30 | 0.2716 | 0.9161 | 0.9065 | 0.8997 | 0.9161 |
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- | 0.0742 | 3.0 | 45 | 0.2662 | 0.9226 | 0.9157 | 0.9091 | 0.9226 |
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- | 0.0453 | 4.0 | 60 | 0.2955 | 0.9226 | 0.9141 | 0.9073 | 0.9226 |
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- | 0.0313 | 5.0 | 75 | 0.2958 | 0.9226 | 0.9157 | 0.9091 | 0.9226 |
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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: 0.3975
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+ - Accuracy: 0.9290
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+ - F1: 0.9219
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+ - Precision: 0.9243
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+ - Recall: 0.9290
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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: 50
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  - eval_batch_size: 50
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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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+ | 0.7867 | 1.0 | 15 | 0.6486 | 0.9161 | 0.9131 | 0.9221 | 0.9161 |
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+ | 0.6021 | 2.0 | 30 | 0.5178 | 0.9226 | 0.9162 | 0.9161 | 0.9226 |
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+ | 0.4997 | 3.0 | 45 | 0.4455 | 0.9226 | 0.9162 | 0.9161 | 0.9226 |
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+ | 0.444 | 4.0 | 60 | 0.4088 | 0.9290 | 0.9219 | 0.9243 | 0.9290 |
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+ | 0.424 | 5.0 | 75 | 0.3975 | 0.9290 | 0.9219 | 0.9243 | 0.9290 |
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  ### Framework versions
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