| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - imdb | |
| metrics: | |
| - accuracy | |
| - f1 | |
| model-index: | |
| - name: finetuning-sentiment-model-3000-samples | |
| results: | |
| - task: | |
| name: Text Classification | |
| type: text-classification | |
| dataset: | |
| name: imdb | |
| type: imdb | |
| args: plain_text | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.8766666666666667 | |
| - name: F1 | |
| type: f1 | |
| value: 0.8825396825396825 | |
| <!-- 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. --> | |
| # finetuning-sentiment-model-3000-samples | |
| 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: 0.3351 | |
| - Accuracy: 0.8767 | |
| - F1: 0.8825 | |
| ## 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 4.17.0 | |
| - Pytorch 1.10.0+cu111 | |
| - Datasets 1.18.4 | |
| - Tokenizers 0.11.6 | |