bert-base-uncased-finetuned-swag
This model is a fine-tuned version of bert-base-uncased on the dream dataset. It achieves the following results on the evaluation set:
- Loss: 1.0986
- Accuracy: 0.3642
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1039 | 1.0 | 3058 | 1.0983 | 0.3779 |
| 1.0995 | 2.0 | 6116 | 1.0986 | 0.3544 |
| 1.1029 | 3.0 | 9174 | 1.0986 | 0.3642 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2