| license: mit | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - imdb | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: gpt2-imdb-sentiment-classifier | |
| results: | |
| - task: | |
| name: Text Classification | |
| type: text-classification | |
| dataset: | |
| name: imdb | |
| type: imdb | |
| args: plain_text | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.9394 | |
| <!-- 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. --> | |
| # gpt2-imdb-sentiment-classifier | |
| This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the imdb dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1703 | |
| - Accuracy: 0.9394 | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| This is comparable to [distilbert-imdb](https://huggingface.co/lvwerra/distilbert-imdb) and trained with exactly the same [script](https://huggingface.co/lvwerra/distilbert-imdb/blob/main/distilbert-imdb-training.ipynb) | |
| It achieves slightly lower loss (0.1703 vs 0.1903) and slightly higher accuracy (0.9394 vs 0.928) | |
| ## 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: 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: 1 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| | 0.1967 | 1.0 | 1563 | 0.1703 | 0.9394 | | |
| ### Framework versions | |
| - Transformers 4.18.0 | |
| - Pytorch 1.13.1+cu117 | |
| - Datasets 2.9.0 | |
| - Tokenizers 0.12.1 | |