--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer datasets: - imdb metrics: - accuracy model-index: - name: N_distilbert_imdb_padding50model results: - task: name: Text Classification type: text-classification dataset: name: imdb type: imdb config: plain_text split: test args: plain_text metrics: - name: Accuracy type: accuracy value: 0.93268 --- # N_distilbert_imdb_padding50model This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset. It achieves the following results on the evaluation set: - Loss: 0.7391 - Accuracy: 0.9327 ## 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: 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: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.2431 | 1.0 | 1563 | 0.2690 | 0.9089 | | 0.1734 | 2.0 | 3126 | 0.2418 | 0.9260 | | 0.1167 | 3.0 | 4689 | 0.4345 | 0.9078 | | 0.0685 | 4.0 | 6252 | 0.3717 | 0.926 | | 0.0445 | 5.0 | 7815 | 0.4502 | 0.9242 | | 0.0338 | 6.0 | 9378 | 0.4786 | 0.9287 | | 0.0293 | 7.0 | 10941 | 0.5332 | 0.9214 | | 0.0191 | 8.0 | 12504 | 0.5435 | 0.9287 | | 0.0182 | 9.0 | 14067 | 0.5450 | 0.9265 | | 0.015 | 10.0 | 15630 | 0.5398 | 0.9297 | | 0.0122 | 11.0 | 17193 | 0.6565 | 0.9226 | | 0.0089 | 12.0 | 18756 | 0.6521 | 0.9280 | | 0.0081 | 13.0 | 20319 | 0.6755 | 0.9285 | | 0.0067 | 14.0 | 21882 | 0.6753 | 0.93 | | 0.0054 | 15.0 | 23445 | 0.7014 | 0.9305 | | 0.0023 | 16.0 | 25008 | 0.7440 | 0.9308 | | 0.0004 | 17.0 | 26571 | 0.7371 | 0.9286 | | 0.0 | 18.0 | 28134 | 0.7497 | 0.9302 | | 0.0004 | 19.0 | 29697 | 0.7386 | 0.9324 | | 0.0002 | 20.0 | 31260 | 0.7391 | 0.9327 | ### Framework versions - Transformers 4.33.2 - Pytorch 2.0.1+cu117 - Datasets 2.14.5 - Tokenizers 0.13.3