metadata
license: mit
base_model: microsoft/BioGPT-Large
tags:
- generated_from_trainer
model-index:
- name: bioGPT
results: []
DoctorGPT
This model is a fine-tuned version of microsoft/BioGPT-Large on a formatted version of the MedQuad-MedicalQnADataset dataset. It achieves the following results on the evaluation set:
- Loss: 1.1114
Model description
The base model used is Microsoft's BioGPT, it was fine-tuned with a custom prompt for a conversational chatbot between a patient and a doctor. The prompt used is as follows:
""" You are a Doctor. Below is a question from a patient. Write a response to the patient that answers their question\n\n"
Patient: {question}"
Doctor: {answer}
"""
Intended uses & limitations
This is a private project for fine-tuning a medical language model, it is not intended to be used as a source medical advice.
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.25 | 51 | 1.2418 |
| 1.3267 | 0.5 | 102 | 1.1900 |
| 1.3267 | 0.75 | 153 | 1.1348 |
| 1.1237 | 0.99 | 204 | 1.0887 |
| 1.1237 | 1.24 | 255 | 1.1018 |
| 0.7527 | 1.49 | 306 | 1.0770 |
| 0.7527 | 1.74 | 357 | 1.0464 |
| 0.7281 | 1.99 | 408 | 1.0233 |
| 0.7281 | 2.24 | 459 | 1.1212 |
| 0.4262 | 2.49 | 510 | 1.1177 |
| 0.4262 | 2.73 | 561 | 1.1125 |
| 0.4124 | 2.98 | 612 | 1.1114 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0