| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: distilbert/distilbert-base-cased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: distilbert-imdb |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # distilbert-imdb |
| |
|
| | This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2111 |
| | - Accuracy: 0.9285 |
| |
|
| | ## 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: 24 |
| | - eval_batch_size: 24 |
| | - 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: 2 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 0.2040 | 0.4997 | 833 | 0.2493 | 0.8981 | |
| | | 0.1805 | 0.9994 | 1666 | 0.2134 | 0.915 | |
| | | 0.1683 | 1.4991 | 2499 | 0.2222 | 0.9262 | |
| | | 0.1644 | 1.9988 | 3332 | 0.2111 | 0.9285 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 5.0.0 |
| | - Pytorch 2.10.0+cu128 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.22.2 |
| | |
