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platzi-distilroberta-base-mrpc-glue-santiago
This model is a fine-tuned version of distilroberta-base on the datasetX dataset. It achieves the following results on the evaluation set:
- Loss: 0.7037
- Accuracy: 0.8137
- F1: 0.8633
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 |
|---|---|---|---|---|---|
| 0.5083 | 1.09 | 500 | 0.7037 | 0.8137 | 0.8633 |
| 0.3404 | 2.18 | 1000 | 0.7367 | 0.8235 | 0.8719 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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Dataset used to train platzi/platzi-distilroberta-base-mrpc-glue-santiago
Evaluation results
- Accuracy on datasetXvalidation set self-reported0.814
- F1 on datasetXvalidation set self-reported0.863