| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: ctc_classifier |
| 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. --> |
|
|
| # ctc_classifier |
| |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [Stanford IMDB dataset](https://ai.stanford.edu/~amaas/data/sentiment/) dataset. |
| |
| ## Model description |
| |
| This is an example model used as part of a class project and I strongly suggest not using it yourself. |
| |
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 2 |
| |
| ### Training results |
| |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.53.2 |
| - Pytorch 2.2.2 |
| - Datasets 4.0.0 |
| - Tokenizers 0.21.2 |
| |
