roberta-base-ca-finetuned-mnli
This model is a fine-tuned version of BSC-TeMU/roberta-base-ca on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4137
- Accuracy: 0.8778
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 |
|---|---|---|---|---|
| 0.3699 | 1.0 | 1255 | 0.3712 | 0.8669 |
| 0.3082 | 2.0 | 2510 | 0.3401 | 0.8766 |
| 0.2375 | 3.0 | 3765 | 0.4137 | 0.8778 |
| 0.1889 | 4.0 | 5020 | 0.4671 | 0.8733 |
| 0.1486 | 5.0 | 6275 | 0.5205 | 0.8749 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.12.1
- Tokenizers 0.10.3
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