roberta-base-bne-finetuned-mnli
This model is a fine-tuned version of BSC-TeMU/roberta-base-bne on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2869
- Accuracy: 0.9012
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 |
|---|---|---|---|---|
| 0.3222 | 1.0 | 1255 | 0.2869 | 0.9012 |
| 0.2418 | 2.0 | 2510 | 0.3125 | 0.8987 |
| 0.1726 | 3.0 | 3765 | 0.4120 | 0.8943 |
| 0.0685 | 4.0 | 5020 | 0.5239 | 0.8919 |
| 0.0245 | 5.0 | 6275 | 0.5910 | 0.8947 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.12.1
- Tokenizers 0.10.3
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