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roberta-large-finetuned-clinc
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: 0.2109
- Accuracy: 0.9703
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: 128
- eval_batch_size: 128
- 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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 5.0643 | 1.0 | 120 | 5.0440 | 0.0065 |
| 4.2726 | 2.0 | 240 | 2.7488 | 0.7255 |
| 1.9687 | 3.0 | 360 | 0.8694 | 0.9174 |
| 0.5773 | 4.0 | 480 | 0.3267 | 0.9539 |
| 0.1842 | 5.0 | 600 | 0.2109 | 0.9703 |
Framework versions
- Transformers 4.19.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.4
- Tokenizers 0.11.6
