MNLI
This model is a fine-tuned version of FacebookAI/roberta-large on the GLUE MNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6192
- Accuracy: 0.8978
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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6.0
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 0.3135 | 1.0 | 6136 | 0.8872 | 0.3194 |
| 0.2281 | 2.0 | 12272 | 0.8983 | 0.3009 |
| 0.1484 | 3.0 | 18408 | 0.9007 | 0.3358 |
| 0.0955 | 4.0 | 24544 | 0.8995 | 0.4247 |
| 0.0616 | 5.0 | 30680 | 0.4938 | 0.8983 |
| 0.0441 | 6.0 | 36816 | 0.6055 | 0.9009 |
Framework versions
- Transformers 4.43.3
- Pytorch 1.11.0+cu113
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
FacebookAI/roberta-large