bert-base-uncased-copa-kb-17
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: 0.6385
- Accuracy: 0.7000
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: 5e-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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 25 | 0.6792 | 0.6500 |
| No log | 2.0 | 50 | 0.6385 | 0.7000 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0