| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - imdb | |
| metrics: | |
| - accuracy | |
| - f1 | |
| base_model: google/bert_uncased_L-4_H-256_A-4 | |
| model-index: | |
| - name: finetuned-base_mini | |
| results: | |
| - task: | |
| type: text-classification | |
| name: Text Classification | |
| dataset: | |
| name: imdb | |
| type: imdb | |
| config: plain_text | |
| split: train | |
| args: plain_text | |
| metrics: | |
| - type: accuracy | |
| value: 0.9076 | |
| name: Accuracy | |
| - type: f1 | |
| value: 0.9515621723631789 | |
| name: F1 | |
| <!-- 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. --> | |
| # finetuned-base_mini | |
| This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on the imdb dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.3938 | |
| - Accuracy: 0.9076 | |
| - F1: 0.9516 | |
| ## 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: 3e-05 | |
| - train_batch_size: 128 | |
| - eval_batch_size: 128 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: constant | |
| - num_epochs: 200 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | |
| | 0.354 | 2.55 | 500 | 0.2300 | 0.9116 | 0.9538 | | |
| | 0.2086 | 5.1 | 1000 | 0.3182 | 0.8815 | 0.9370 | | |
| | 0.1401 | 7.65 | 1500 | 0.2160 | 0.9241 | 0.9605 | | |
| | 0.0902 | 10.2 | 2000 | 0.4684 | 0.8722 | 0.9317 | | |
| | 0.0654 | 12.76 | 2500 | 0.4885 | 0.8747 | 0.9332 | | |
| | 0.043 | 15.31 | 3000 | 0.3938 | 0.9076 | 0.9516 | | |
| ### Framework versions | |
| - Transformers 4.25.0 | |
| - Pytorch 1.12.1+cu113 | |
| - Datasets 2.7.1 | |
| - Tokenizers 0.13.2 | |