transfer-course-distilroberta-base-mrpc-glue-nestor-mamani
This model is a fine-tuned version of distilroberta-base on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.4601
- Accuracy: 0.8358
- F1: 0.8859
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: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.315 | 2.17 | 500 | 0.4601 | 0.8358 | 0.8859 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.14.1
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Finetuned from
Dataset used to train platzi/transfer-course-distilroberta-base-mrpc-glue-nestor-mamani
Evaluation results
- Accuracy on gluevalidation set self-reported0.836
- F1 on gluevalidation set self-reported0.886