platzi-diltilroberta-base-mrpc-glue-santiago-toledo
This model is a fine-tuned version of distilroberta-base on the datasetX dataset. It achieves the following results on the evaluation set:
- Loss: 0.6731
- Accuracy: 0.8284
- F1: 0.8723
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 |
|---|---|---|---|---|---|
| 0.4044 | 1.09 | 500 | 0.6731 | 0.8284 | 0.8723 |
| 0.231 | 2.18 | 1000 | 0.8025 | 0.8260 | 0.8748 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cpu
- Datasets 2.14.4
- Tokenizers 0.13.3