This model is a fine-tuned version of microsoft/deberta-v3-large on the GLUE MNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.4103
- Accuracy: 0.9175
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 6e-06
- 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
- lr_scheduler_warmup_steps: 50
- num_epochs: 2.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3631 | 1.0 | 49088 | 0.3129 | 0.9130 |
| 0.2267 | 2.0 | 98176 | 0.4157 | 0.9153 |
Framework versions
- Transformers 4.13.0.dev0
- Pytorch 1.10.0
- Datasets 1.15.2.dev0
- Tokenizers 0.10.3
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