distilbert-base-uncased-finetuned-imdb
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3800
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Step | Training Loss | Validation Loss | Perplexity |
|---|---|---|---|
| 156 | 2.458119 | — | — |
| 312 | 2.440733 | — | — |
| 468 | 2.415128 | — | — |
| 471 | 2.415128 | 2.379980 | 10.80 |
Framework versions
- Transformers 5.15.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
Usage
preds = mask_filler(text)
for pred in preds:
print(f"{pred['sequence']}")
preds = mask_filler(text)
for pred in preds:
print(f"{pred['sequence']}")
Output
- this is a great film.
- this is a great movie.
- this is a great idea.
- this is a great one.
- this is a great story.