classificacao_texto_hugging_face
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3584
- Accuracy: 0.9328
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2252 | 1.0 | 1563 | 0.2360 | 0.9062 |
| 0.1526 | 2.0 | 3126 | 0.2298 | 0.9292 |
| 0.0893 | 3.0 | 4689 | 0.2804 | 0.9330 |
| 0.0489 | 4.0 | 6252 | 0.3457 | 0.9317 |
| 0.0337 | 5.0 | 7815 | 0.3584 | 0.9328 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2
- Datasets 3.0.0
- Tokenizers 0.19.1