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AAMartinez
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hate_BERTimbau_v3

Text Classification
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bert
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End of training

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  1. README.md +13 -11
  2. model.safetensors +1 -1
  3. runs/Jun11_11-13-19_ade33af8e696/events.out.tfevents.1718104400.ade33af8e696.876.1 +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: 0.7036
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- - Precision: 0.7549
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- - Recall: 0.7549
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- - F1: 0.7549
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- - Accuracy: 0.7549
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  ## Model description
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@@ -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: 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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- | 0.5537 | 1.0 | 284 | 0.4903 | 0.7478 | 0.7478 | 0.7478 | 0.7478 |
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- | 0.4521 | 2.0 | 568 | 0.4700 | 0.7725 | 0.7725 | 0.7725 | 0.7725 |
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- | 0.3673 | 3.0 | 852 | 0.5629 | 0.7443 | 0.7443 | 0.7443 | 0.7443 |
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- | 0.2873 | 4.0 | 1136 | 0.5845 | 0.7690 | 0.7690 | 0.7690 | 0.7690 |
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- | 0.2047 | 5.0 | 1420 | 0.7036 | 0.7549 | 0.7549 | 0.7549 | 0.7549 |
 
 
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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: 1.7782
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+ - Precision: 0.7641
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+ - Recall: 0.7690
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+ - F1: 0.7621
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+ - Accuracy: 0.7690
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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
 
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.5887 | 1.0 | 284 | 0.5397 | 0.7478 | 0.7319 | 0.7362 | 0.7319 |
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+ | 0.4617 | 2.0 | 568 | 0.4880 | 0.7842 | 0.7090 | 0.7136 | 0.7090 |
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+ | 0.3256 | 3.0 | 852 | 0.7394 | 0.7646 | 0.7690 | 0.7603 | 0.7690 |
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+ | 0.2023 | 4.0 | 1136 | 0.8880 | 0.7808 | 0.7831 | 0.7816 | 0.7831 |
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+ | 0.1305 | 5.0 | 1420 | 1.0510 | 0.7747 | 0.7619 | 0.7654 | 0.7619 |
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+ | 0.0916 | 6.0 | 1704 | 1.4921 | 0.7452 | 0.7496 | 0.7464 | 0.7496 |
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+ | 0.0494 | 7.0 | 1988 | 1.7782 | 0.7641 | 0.7690 | 0.7621 | 0.7690 |
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  ### Framework versions
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