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AAMartinez
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hate_BERTimbau_v1

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/Jun10_15-34-54_feeb7bdd688d/events.out.tfevents.1718033696.feeb7bdd688d.433.0 +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: 1.1746
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- - Precision: 0.7707
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- - Recall: 0.7707
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- - F1: 0.7707
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- - Accuracy: 0.7707
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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: 5e-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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- | 0.5246 | 1.0 | 284 | 0.4708 | 0.7707 | 0.7707 | 0.7707 | 0.7707 |
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- | 0.394 | 2.0 | 568 | 0.4454 | 0.7919 | 0.7919 | 0.7919 | 0.7919 |
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- | 0.2585 | 3.0 | 852 | 0.8828 | 0.7407 | 0.7407 | 0.7407 | 0.7407 |
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- | 0.153 | 4.0 | 1136 | 1.1051 | 0.7372 | 0.7372 | 0.7372 | 0.7372 |
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- | 0.0935 | 5.0 | 1420 | 1.1746 | 0.7707 | 0.7707 | 0.7707 | 0.7707 |
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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: 1.0655
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+ - Precision: 0.7690
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+ - Recall: 0.7690
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+ - F1: 0.7690
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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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+ | 0.5264 | 1.0 | 284 | 0.5050 | 0.7619 | 0.7619 | 0.7619 | 0.7619 |
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+ | 0.4133 | 2.0 | 568 | 0.4516 | 0.7937 | 0.7937 | 0.7937 | 0.7937 |
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+ | 0.289 | 3.0 | 852 | 0.6485 | 0.7531 | 0.7531 | 0.7531 | 0.7531 |
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+ | 0.1804 | 4.0 | 1136 | 0.7828 | 0.7813 | 0.7813 | 0.7813 | 0.7813 |
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+ | 0.1147 | 5.0 | 1420 | 1.0655 | 0.7690 | 0.7690 | 0.7690 | 0.7690 |
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  ### Framework versions
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