deep_model_09_clasificador-news
This model is a fine-tuned version of bert-base-uncased on the ag_news dataset. It achieves the following results on the evaluation set:
- Loss: 0.3664
- Accuracy: 0.9290
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3384 | 1.0 | 2500 | 0.3871 | 0.9053 |
| 0.208 | 2.0 | 5000 | 0.3549 | 0.9171 |
| 0.0861 | 3.0 | 7500 | 0.3664 | 0.9290 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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Dataset used to train Alesteba/deep_model_09_clasificador-news
Evaluation results
- Accuracy on ag_newstest set self-reported0.929