fine-tuned-distilbert-base-uncased-swag
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the swag dataset. It achieves the following results on the evaluation set:
- Loss: 0.8217
- Accuracy: 0.7282
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: 1.5e-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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.8947 | 1.0 | 4597 | 0.7623 | 0.6946 |
| 0.6717 | 2.0 | 9194 | 0.7162 | 0.7186 |
| 0.514 | 3.0 | 13791 | 0.7402 | 0.7261 |
| 0.4048 | 4.0 | 18388 | 0.8217 | 0.7282 |
Framework versions
- Transformers 4.41.2
- Pytorch 1.11.0
- Datasets 2.19.1
- Tokenizers 0.19.1
- Downloads last month
- 5
Inference API (serverless) does not yet support transformers models for this pipeline type.
Model tree for amritpuhan/fine-tuned-distilbert-base-uncased-swag
Base model
distilbert/distilbert-base-uncased