| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-bert/bert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: bert-wellness-classifier_teacher |
| 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. --> |
|
|
| # bert-wellness-classifier_teacher |
| |
| 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: 0.7694 |
| - Accuracy: 0.688 |
| - Auc: 0.9 |
| - Precision Class 0: 0.862 |
| - Precision Class 1: 0.739 |
| - Precision Class 2: 0.613 |
| - Precision Class 3: 0.538 |
| - Recall Class 0: 0.781 |
| - Recall Class 1: 0.81 |
| - Recall Class 2: 0.704 |
| - Recall Class 3: 0.483 |
| |
| ## 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: 0.0002 |
| - 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 |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | Precision Class 0 | Precision Class 1 | Precision Class 2 | Precision Class 3 | Recall Class 0 | Recall Class 1 | Recall Class 2 | Recall Class 3 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:-----------------:|:-----------------:|:-----------------:|:-----------------:|:--------------:|:--------------:|:--------------:|:--------------:| |
| | 1.3247 | 1.0 | 63 | 1.1856 | 0.569 | 0.819 | 0.759 | 0.727 | 0.414 | 0.727 | 0.688 | 0.381 | 0.889 | 0.276 | |
| | 1.0767 | 2.0 | 126 | 1.0166 | 0.587 | 0.857 | 0.667 | 0.643 | 1.0 | 0.462 | 0.75 | 0.429 | 0.259 | 0.828 | |
| | 0.9285 | 3.0 | 189 | 0.9616 | 0.633 | 0.875 | 0.846 | 0.486 | 1.0 | 0.528 | 0.688 | 0.857 | 0.37 | 0.655 | |
| | 0.8628 | 4.0 | 252 | 0.8910 | 0.624 | 0.885 | 0.88 | 0.514 | 0.64 | 0.5 | 0.688 | 0.857 | 0.593 | 0.414 | |
| | 0.7828 | 5.0 | 315 | 0.8369 | 0.679 | 0.888 | 0.88 | 0.667 | 0.75 | 0.514 | 0.688 | 0.857 | 0.556 | 0.655 | |
| | 0.7489 | 6.0 | 378 | 0.7962 | 0.706 | 0.899 | 0.857 | 0.762 | 0.704 | 0.545 | 0.75 | 0.762 | 0.704 | 0.621 | |
| | 0.6981 | 7.0 | 441 | 0.8118 | 0.679 | 0.896 | 0.88 | 0.708 | 0.633 | 0.533 | 0.688 | 0.81 | 0.704 | 0.552 | |
| | 0.6634 | 8.0 | 504 | 0.7915 | 0.688 | 0.898 | 0.889 | 0.708 | 0.655 | 0.517 | 0.75 | 0.81 | 0.704 | 0.517 | |
| | 0.6651 | 9.0 | 567 | 0.7777 | 0.67 | 0.9 | 0.862 | 0.739 | 0.576 | 0.5 | 0.781 | 0.81 | 0.704 | 0.414 | |
| | 0.6591 | 10.0 | 630 | 0.7694 | 0.688 | 0.9 | 0.862 | 0.739 | 0.613 | 0.538 | 0.781 | 0.81 | 0.704 | 0.483 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.45.1 |
| - Pytorch 2.4.0+cpu |
| - Datasets 3.0.1 |
| - Tokenizers 0.20.0 |
| |
