microtest-2.0
This model is a fine-tuned version of bert-base-uncased on the azaheadhealth dataset. It achieves the following results on the evaluation set:
- Loss: 0.3672
- Accuracy: 0.75
- F1: 0.8
- Precision: 0.6667
- 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 |
|---|---|---|---|---|---|---|---|
| 0.8113 | 0.5 | 1 | 0.4486 | 0.75 | 0.8 | 0.6667 | 1.0 |
| 0.7227 | 1.0 | 2 | 0.3672 | 0.75 | 0.8 | 0.6667 | 1.0 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.13.2
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Model tree for zwellington/microtest-2.0
Base model
google-bert/bert-base-uncasedEvaluation results
- Accuracy on azaheadhealthtest set self-reported0.750
- F1 on azaheadhealthtest set self-reported0.800
- Precision on azaheadhealthtest set self-reported0.667
- Recall on azaheadhealthtest set self-reported1.000