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AAMartinez
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hate_BERTimbau_v2

Text Classification
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bert
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End of training

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  1. README.md +11 -11
  2. model.safetensors +1 -1
  3. runs/Jun11_10-24-00_5248e87620aa/events.out.tfevents.1718101441.5248e87620aa.12516.0 +2 -2
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 [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1038
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- - Precision: 0.7478
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- - Recall: 0.7478
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- - F1: 0.7478
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- - Accuracy: 0.7478
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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: 16
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  - eval_batch_size: 16
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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 | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.5312 | 1.0 | 284 | 0.4975 | 0.7584 | 0.7584 | 0.7584 | 0.7584 |
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- | 0.4143 | 2.0 | 568 | 0.4635 | 0.7813 | 0.7813 | 0.7813 | 0.7813 |
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- | 0.2898 | 3.0 | 852 | 0.6093 | 0.7619 | 0.7619 | 0.7619 | 0.7619 |
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- | 0.1713 | 4.0 | 1136 | 0.8976 | 0.7637 | 0.7637 | 0.7637 | 0.7637 |
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- | 0.113 | 5.0 | 1420 | 1.1038 | 0.7478 | 0.7478 | 0.7478 | 0.7478 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6805
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+ - Precision: 0.7854
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+ - Recall: 0.7743
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+ - F1: 0.7774
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+ - Accuracy: 0.7743
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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: 1e-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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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.5478 | 1.0 | 284 | 0.4797 | 0.7607 | 0.7654 | 0.7612 | 0.7654 |
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+ | 0.4446 | 2.0 | 568 | 0.4527 | 0.7868 | 0.7901 | 0.7873 | 0.7901 |
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+ | 0.3613 | 3.0 | 852 | 0.5176 | 0.7704 | 0.7707 | 0.7573 | 0.7707 |
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+ | 0.276 | 4.0 | 1136 | 0.6189 | 0.7663 | 0.7707 | 0.7628 | 0.7707 |
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+ | 0.1998 | 5.0 | 1420 | 0.6805 | 0.7854 | 0.7743 | 0.7774 | 0.7743 |
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  ### Framework versions
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