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--- |
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library_name: transformers |
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license: mit |
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base_model: neuralmind/bert-base-portuguese-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: BingoGuard-bert-base-base-plus-custom |
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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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# BingoGuard-bert-base-base-plus-custom |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6610 |
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- Accuracy: 0.8766 |
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- F1: 0.8745 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.381 | 1.0 | 67 | 0.2833 | 0.9 | 0.8920 | |
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| 0.2434 | 2.0 | 134 | 0.3236 | 0.8979 | 0.8943 | |
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| 0.1175 | 3.0 | 201 | 0.4126 | 0.8702 | 0.8737 | |
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| 0.06 | 4.0 | 268 | 0.6708 | 0.8426 | 0.852 | |
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| 0.0495 | 5.0 | 335 | 0.5486 | 0.8766 | 0.8728 | |
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| 0.0187 | 6.0 | 402 | 0.6512 | 0.8787 | 0.8779 | |
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| 0.0072 | 7.0 | 469 | 0.6511 | 0.8745 | 0.8709 | |
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| 0.0375 | 8.0 | 536 | 0.6610 | 0.8766 | 0.8745 | |
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### Framework versions |
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- Transformers 4.55.4 |
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- Pytorch 2.8.0+cu128 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.4 |
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