bert-base-uncased-finetuned-swag
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3863
- Accuracy: 0.2077
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3975 | 1.0 | 6316 | 1.3863 | 0.2637 |
| 1.3898 | 2.0 | 12632 | 1.3863 | 0.1595 |
| 1.3898 | 3.0 | 18948 | 1.3863 | 0.2077 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for Rambo-007/bert-base-uncased-finetuned-swag
Base model
google-bert/bert-base-uncased