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roberta-large-finetuned-clinc-12
This model is a fine-tuned version of roberta-large on the clinc_oos dataset. It achieves the following results on the evaluation set:
- Loss: 0.1429
- Accuracy: 0.9765
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
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.8662 | 1.0 | 954 | 0.3441 | 0.9339 |
| 0.158 | 2.0 | 1908 | 0.1498 | 0.9742 |
| 0.0469 | 3.0 | 2862 | 0.1429 | 0.9765 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.2+cu113
- Datasets 1.18.4
- Tokenizers 0.11.6
