bert-base-uncased-copa-kb-27
This model is a fine-tuned version of bert-base-uncased on the super_glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.6114
- Accuracy: 0.7100
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 40 | 0.6534 | 0.7400 |
| No log | 2.0 | 80 | 0.6114 | 0.7100 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
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