Prueba4
This model is a fine-tuned version of distilroberta-base on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 1.1542
- Accuracy: 0.8407
- F1: 0.8845
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 |
---|---|---|---|---|---|
0.0931 | 1.09 | 500 | 1.1624 | 0.8260 | 0.8807 |
0.0917 | 2.18 | 1000 | 1.1542 | 0.8407 | 0.8845 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Downloads last month
- 13
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
Dataset used to train Saul98lm/Prueba4
Evaluation results
- Accuracy on gluevalidation set self-reported0.841
- F1 on gluevalidation set self-reported0.885