roberta-mnli-finetune-config
This model is a fine-tuned version of roberta-large-mnli on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6113
- Accuracy: 0.8673
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5638 | 1.0 | 10108 | 0.5104 | 0.8584 |
| 0.4304 | 2.0 | 20216 | 0.6113 | 0.8673 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
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