bert-base-uncased-finetuned-swag
This model is a fine-tuned version of bert-base-uncased on the swag dataset. It achieves the following results on the evaluation set:
- Loss: 0.7187
- Accuracy: 0.7223
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|
| 0.9645 | 1.0 | 2299 | 0.7779 | 0.6998 |
| 0.8942 | 2.0 | 4598 | 0.7322 | 0.7184 |
| 0.8907 | 3.0 | 6897 | 0.7187 | 0.7223 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.3
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Model tree for NightMachinery/bert-base-uncased-finetuned-swag
Base model
google-bert/bert-base-uncased