| --- |
| library_name: transformers |
| license: mit |
| base_model: roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: roberta-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. --> |
|
|
| # roberta-wellness-classifier |
|
|
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.8807 |
| - Accuracy: 0.71 |
| - Auc: 0.871 |
| - Precision Class 0: 0.787 |
| - Precision Class 1: 0.857 |
| - Precision Class 2: 0.731 |
| - Precision Class 3: 0.645 |
| - Recall Class 0: 0.698 |
| - Recall Class 1: 0.667 |
| - Recall Class 2: 0.603 |
| - Recall Class 3: 0.796 |
|
|
| ## 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: 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:-----------------:|:-----------------:|:-----------------:|:-----------------:|:--------------:|:--------------:|:--------------:|:--------------:| |
| | 1.0423 | 1.0 | 140 | 0.7782 | 0.685 | 0.888 | 0.732 | 0.727 | 0.595 | 0.734 | 0.774 | 0.593 | 0.794 | 0.592 | |
| | 0.6558 | 2.0 | 280 | 0.7589 | 0.714 | 0.902 | 0.733 | 0.85 | 0.78 | 0.658 | 0.83 | 0.63 | 0.508 | 0.806 | |
| | 0.4306 | 3.0 | 420 | 1.0251 | 0.73 | 0.89 | 0.738 | 0.857 | 0.64 | 0.795 | 0.849 | 0.667 | 0.873 | 0.592 | |
| | 0.3002 | 4.0 | 560 | 1.2314 | 0.726 | 0.908 | 0.816 | 0.938 | 0.707 | 0.669 | 0.755 | 0.556 | 0.651 | 0.806 | |
| | 0.2117 | 5.0 | 700 | 1.3601 | 0.714 | 0.888 | 0.857 | 0.941 | 0.645 | 0.67 | 0.679 | 0.593 | 0.778 | 0.724 | |
| | 0.1606 | 6.0 | 840 | 1.4648 | 0.718 | 0.887 | 0.784 | 0.933 | 0.682 | 0.679 | 0.755 | 0.519 | 0.714 | 0.755 | |
| | 0.1135 | 7.0 | 980 | 1.6228 | 0.714 | 0.883 | 0.78 | 0.826 | 0.698 | 0.667 | 0.736 | 0.704 | 0.698 | 0.714 | |
| | 0.0686 | 8.0 | 1120 | 1.8947 | 0.71 | 0.866 | 0.809 | 0.857 | 0.745 | 0.635 | 0.717 | 0.667 | 0.556 | 0.816 | |
| | 0.0525 | 9.0 | 1260 | 1.8817 | 0.718 | 0.875 | 0.796 | 0.864 | 0.74 | 0.65 | 0.736 | 0.704 | 0.587 | 0.796 | |
| | 0.0526 | 10.0 | 1400 | 1.8807 | 0.71 | 0.871 | 0.787 | 0.857 | 0.731 | 0.645 | 0.698 | 0.667 | 0.603 | 0.796 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.45.1 |
| - Pytorch 2.4.0 |
| - Datasets 3.0.1 |
| - Tokenizers 0.20.0 |
|
|
