metadata
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: medical-diagnosis-classification-model
results: []
medical-diagnosis-classification-model
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8962
- Accuracy: 0.5784
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: 5e-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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9083 | 0.44 | 5000 | 0.9480 | 0.5413 |
| 0.9345 | 0.87 | 10000 | 0.9236 | 0.5690 |
| 0.9558 | 1.31 | 15000 | 0.9112 | 0.5633 |
| 1.0294 | 1.75 | 20000 | 0.9150 | 0.5629 |
| 1.0029 | 2.18 | 25000 | 0.9197 | 0.5547 |
| 0.8028 | 2.62 | 30000 | 0.9018 | 0.5689 |
| 0.8739 | 3.06 | 35000 | 0.8926 | 0.5844 |
| 0.9352 | 3.49 | 40000 | 0.8988 | 0.5753 |
| 0.9041 | 3.93 | 45000 | 0.9014 | 0.5731 |
| 0.8445 | 4.37 | 50000 | 0.8990 | 0.5744 |
| 0.8374 | 4.8 | 55000 | 0.8962 | 0.5784 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0