platzi-distilroberta-base-mrpc-glue-gabriel-salazar
This model is a fine-tuned version of distilroberta-base on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.8225
- Accuracy: 0.8529
- F1: 0.8966
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 |
|---|---|---|---|---|---|
| 0.3159 | 1.09 | 500 | 0.8118 | 0.8284 | 0.8793 |
| 0.1736 | 2.18 | 1000 | 0.8225 | 0.8529 | 0.8966 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
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Model tree for platzi/platzi-distilroberta-base-mrpc-glue-gabriel-salazar
Base model
distilbert/distilroberta-baseDataset used to train platzi/platzi-distilroberta-base-mrpc-glue-gabriel-salazar
Evaluation results
- Accuracy on gluevalidation set self-reported0.853
- F1 on gluevalidation set self-reported0.897