distilbert-base-uncased-finetuned-mnli
This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.6574
- Accuracy: 0.8205
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5188 | 1.0 | 24544 | 0.4979 | 0.8047 |
| 0.4153 | 2.0 | 49088 | 0.4845 | 0.8147 |
| 0.3008 | 3.0 | 73632 | 0.5631 | 0.8204 |
| 0.2226 | 4.0 | 98176 | 0.6574 | 0.8205 |
| 0.189 | 5.0 | 122720 | 0.8209 | 0.8194 |
Framework versions
- Transformers 4.19.4
- Pytorch 1.11.0+cu113
- Datasets 2.3.0
- Tokenizers 0.12.1
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