--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: finetuning-DistillBERT-3000-samples results: [] datasets: - imdb --- # finetuning-DistillBERT-3000-samples This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [IMDB](https://huggingface.co/datasets/imdb) dataset. It achieves the following results on the evaluation set: - Loss: 0.3396 - Accuracy: 0.87 - F1: 0.8730 ## 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: 2 ### Training results ### Framework versions - Transformers 4.38.1 - Pytorch 2.1.0+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2