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--- |
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library_name: transformers |
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license: mit |
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base_model: belisards/congretimbau |
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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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- recall |
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- precision |
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model-index: |
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- name: MyDrive |
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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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# MyDrive |
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This model is a fine-tuned version of [belisards/congretimbau](https://huggingface.co/belisards/congretimbau) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1336 |
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- Accuracy: 0.8776 |
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- F1: 0.8115 |
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- Recall: 0.7919 |
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- Precision: 0.8389 |
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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: 1e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 5151 |
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- optimizer: Use adamw_torch 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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- lr_scheduler_warmup_steps: 150 |
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- num_epochs: 14 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
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| 0.1343 | 2.8333 | 51 | 0.1396 | 0.7679 | 0.5492 | 0.5629 | 0.7832 | |
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| 0.1057 | 5.6667 | 102 | 0.1280 | 0.8036 | 0.6777 | 0.6543 | 0.7887 | |
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| 0.053 | 8.5 | 153 | 0.1457 | 0.8482 | 0.7899 | 0.7742 | 0.8125 | |
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| 0.0159 | 11.3333 | 204 | 0.2345 | 0.8482 | 0.7952 | 0.7854 | 0.8072 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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