| --- |
| license: apache-2.0 |
| base_model: bert-base-uncased |
| tags: |
| - generated_from_trainer |
| datasets: |
| - azaheadhealth |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: microtest |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: azaheadhealth |
| type: azaheadhealth |
| config: micro |
| split: test |
| args: micro |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 1.0 |
| - name: F1 |
| type: f1 |
| value: 1.0 |
| - name: Precision |
| type: precision |
| value: 1.0 |
| - name: Recall |
| type: recall |
| value: 1.0 |
| --- |
| |
| <!-- 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. --> |
|
|
| # microtest |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the azaheadhealth dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6111 |
| - Accuracy: 1.0 |
| - F1: 1.0 |
| - Precision: 1.0 |
| - Recall: 1.0 |
|
|
| ## 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: 1 |
| - eval_batch_size: 1 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 2 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 1 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:---------:|:------:| |
| | 0.5955 | 0.5 | 1 | 0.6676 | 0.5 | 0.5 | 0.5 | 0.5 | |
| | 0.633 | 1.0 | 2 | 0.6111 | 1.0 | 1.0 | 1.0 | 1.0 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.31.0 |
| - Pytorch 2.2.0+cu121 |
| - Datasets 2.16.1 |
| - Tokenizers 0.13.2 |
| |
