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platzi-bert-base-mrpc-glue-omar-espejel
This model is a fine-tuned version of bert-base-uncased on the glue and the mrpc datasets. It achieves the following results on the evaluation set:
- Loss: 0.4366
- Accuracy: 0.8578
- F1: 0.8942
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5221 | 1.09 | 500 | 0.4366 | 0.8578 | 0.8942 |
| 0.3114 | 2.18 | 1000 | 0.6581 | 0.8725 | 0.9113 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
