<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
clasificador-sms
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0286
- Accuracy: 0.9964
Model description
Se cree que arroja un acuraccy tan bueno porque las clases están desbalanceadas, como no era el objetivo de la asignatura no se indagado más sobre este problema
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 |
|---|---|---|---|---|
| 0.0805 | 1.0 | 627 | 0.0328 | 0.9928 |
| 0.0343 | 2.0 | 1254 | 0.0180 | 0.9964 |
| 0.0132 | 3.0 | 1881 | 0.0286 | 0.9964 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
