| --- |
| library_name: transformers |
| license: cc-by-nc-4.0 |
| base_model: mental/mental-bert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: mentalBERT-wellness-classifier |
| 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. --> |
|
|
| # mentalBERT-wellness-classifier |
|
|
| This model is a fine-tuned version of [mental/mental-bert-base-uncased](https://huggingface.co/mental/mental-bert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.0471 |
| - Accuracy: 0.722 |
| - Auc: 0.915 |
| - Precision Class 0: 0.765 |
| - Precision Class 1: 0.762 |
| - Precision Class 2: 0.745 |
| - Precision Class 3: 0.684 |
| - Recall Class 0: 0.736 |
| - Recall Class 1: 0.593 |
| - Recall Class 2: 0.651 |
| - Recall Class 3: 0.796 |
| - F1 Score Class 0: 0.75 |
| - F1 Score Class 1: 0.667 |
| - F1 Score Class 2: 0.695 |
| - F1 Score Class 3: 0.736 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
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|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| 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 |
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|
| | 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 | F1 Score Class 0 | F1 Score Class 1 | F1 Score Class 2 | F1 Score Class 3 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:-----------------:|:-----------------:|:-----------------:|:-----------------:|:--------------:|:--------------:|:--------------:|:--------------:|:----------------:|:----------------:|:----------------:|:----------------:| |
| | 0.0887 | 1.0 | 140 | 1.2702 | 0.73 | 0.91 | 0.783 | 0.773 | 0.746 | 0.693 | 0.679 | 0.63 | 0.698 | 0.806 | 0.727 | 0.694 | 0.721 | 0.745 | |
| | 0.2058 | 2.0 | 280 | 1.0340 | 0.718 | 0.916 | 0.75 | 0.72 | 0.736 | 0.694 | 0.736 | 0.667 | 0.619 | 0.786 | 0.743 | 0.692 | 0.672 | 0.737 | |
| | 0.1921 | 3.0 | 420 | 1.0234 | 0.739 | 0.919 | 0.733 | 0.731 | 0.75 | 0.737 | 0.83 | 0.704 | 0.667 | 0.745 | 0.779 | 0.717 | 0.706 | 0.741 | |
| | 0.184 | 4.0 | 560 | 1.0486 | 0.73 | 0.917 | 0.719 | 0.773 | 0.738 | 0.723 | 0.774 | 0.63 | 0.714 | 0.745 | 0.745 | 0.694 | 0.726 | 0.734 | |
| | 0.1666 | 5.0 | 700 | 1.0084 | 0.747 | 0.918 | 0.769 | 0.739 | 0.738 | 0.743 | 0.755 | 0.63 | 0.762 | 0.765 | 0.762 | 0.68 | 0.75 | 0.754 | |
| | 0.1558 | 6.0 | 840 | 1.0314 | 0.739 | 0.917 | 0.759 | 0.773 | 0.738 | 0.721 | 0.774 | 0.63 | 0.714 | 0.765 | 0.766 | 0.694 | 0.726 | 0.743 | |
| | 0.138 | 7.0 | 980 | 1.0733 | 0.73 | 0.915 | 0.776 | 0.773 | 0.75 | 0.693 | 0.717 | 0.63 | 0.667 | 0.806 | 0.745 | 0.694 | 0.706 | 0.745 | |
| | 0.1481 | 8.0 | 1120 | 1.0656 | 0.722 | 0.914 | 0.787 | 0.773 | 0.741 | 0.678 | 0.698 | 0.63 | 0.635 | 0.816 | 0.74 | 0.694 | 0.684 | 0.741 | |
| | 0.1433 | 9.0 | 1260 | 1.0520 | 0.718 | 0.915 | 0.765 | 0.762 | 0.741 | 0.678 | 0.736 | 0.593 | 0.635 | 0.796 | 0.75 | 0.667 | 0.684 | 0.732 | |
| | 0.1577 | 10.0 | 1400 | 1.0471 | 0.722 | 0.915 | 0.765 | 0.762 | 0.745 | 0.684 | 0.736 | 0.593 | 0.651 | 0.796 | 0.75 | 0.667 | 0.695 | 0.736 | |
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| ### Framework versions |
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|
| - Transformers 4.45.1 |
| - Pytorch 2.4.0 |
| - Datasets 3.0.1 |
| - Tokenizers 0.20.0 |
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