classificacao_texto_hugging_face_v1
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: 0.3487
- Accuracy: 0.9329
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 |
|---|---|---|---|---|
| 0.2281 | 1.0 | 1563 | 0.2264 | 0.9129 |
| 0.1569 | 2.0 | 3126 | 0.2086 | 0.9316 |
| 0.0937 | 3.0 | 4689 | 0.2765 | 0.9332 |
| 0.0539 | 4.0 | 6252 | 0.3649 | 0.9253 |
| 0.0333 | 5.0 | 7815 | 0.3487 | 0.9329 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1