| --- |
| license: apache-2.0 |
| base_model: google-bert/bert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: fine_tuned_boolq_bert |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # fine_tuned_boolq_bert |
| |
| This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.5736 |
| - Accuracy: 0.7222 |
| - F1: 0.7325 |
| |
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - training_steps: 400 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:| |
| | 0.6443 | 4.1667 | 50 | 0.5606 | 0.7778 | 0.6806 | |
| | 0.3932 | 8.3333 | 100 | 0.6016 | 0.6111 | 0.6255 | |
| | 0.126 | 12.5 | 150 | 1.0887 | 0.5 | 0.5418 | |
| | 0.0166 | 16.6667 | 200 | 1.5543 | 0.5556 | 0.5829 | |
| | 0.0041 | 20.8333 | 250 | 1.5032 | 0.7222 | 0.7325 | |
| | 0.0022 | 25.0 | 300 | 1.7354 | 0.6667 | 0.6872 | |
| | 0.0018 | 29.1667 | 350 | 1.5756 | 0.6667 | 0.6667 | |
| | 0.0016 | 33.3333 | 400 | 1.5736 | 0.7222 | 0.7325 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.1 |
| - Pytorch 2.3.0 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
| |
