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--- |
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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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model-index: |
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- name: file_classifier_v3 |
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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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# file_classifier_v3 |
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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: 0.6714 |
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- Accuracy: 0.8586 |
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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: 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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 73 | 0.7821 | 0.7966 | |
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| No log | 2.0 | 146 | 0.7362 | 0.8103 | |
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| No log | 3.0 | 219 | 0.6557 | 0.8207 | |
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| No log | 4.0 | 292 | 0.7113 | 0.8069 | |
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| No log | 5.0 | 365 | 0.6241 | 0.8379 | |
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| No log | 6.0 | 438 | 0.6169 | 0.8448 | |
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| 0.206 | 7.0 | 511 | 0.6305 | 0.8345 | |
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| 0.206 | 8.0 | 584 | 0.6552 | 0.8621 | |
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| 0.206 | 9.0 | 657 | 0.6110 | 0.8724 | |
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| 0.206 | 10.0 | 730 | 0.6937 | 0.8552 | |
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| 0.206 | 11.0 | 803 | 0.6749 | 0.8552 | |
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| 0.206 | 12.0 | 876 | 0.6484 | 0.8690 | |
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| 0.206 | 13.0 | 949 | 0.6889 | 0.8586 | |
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| 0.0253 | 14.0 | 1022 | 0.6630 | 0.8586 | |
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| 0.0253 | 15.0 | 1095 | 0.6714 | 0.8586 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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