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---
base_model: unsloth/Meta-Llama-3.1-8B
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
- sft
---
# MedGPT-Llama3.1-8B-v.1
- This model is a fine-tuned version of [unsloth/Meta-Llama-3.1-8B](https://huggingface.co/unsloth/Meta-Llama-3.1-8B) on an dataset created by [Valerio Job](https://huggingface.co/valeriojob) together with GPs based on real medical data.
- Version 1 (v.1) of MedGPT is the very first version of MedGPT and the training dataset has been kept simple and small with only 60 examples.
- This repo includes the 16bit format of the model as well as the LoRA adapters of the model. There is a separate repo called [valeriojob/MedGPT-Llama3.1-8B-BA-v.1-GGUF](https://huggingface.co/valeriojob/MedGPT-Llama3.1-8B-BA-v.1-GGUF) that includes the quantized versions of this model in GGUF format.
- This model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
## Model description
This model acts as a supplementary assistance to GPs helping them in medical and admin tasks.
## Intended uses & limitations
The fine-tuned model should not be used in production! This model has been created as a initial prototype in the context of a bachelor thesis.
## Training and evaluation data
The dataset (train and test) used for fine-tuning this model can be found here: [datasets/valeriojob/BA-v.1](https://huggingface.co/datasets/valeriojob/BA-v.1)
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- per_device_train_batch_size = 2,
- gradient_accumulation_steps = 4,
- warmup_steps = 5,
- max_steps = 60,
- learning_rate = 2e-4,
- fp16 = not is_bfloat16_supported(),
- bf16 = is_bfloat16_supported(),
- logging_steps = 1,
- optim = "adamw_8bit",
- weight_decay = 0.01,
- lr_scheduler_type = "linear",
- seed = 3407,
- output_dir = "outputs"
### Training results
| Training Loss | Step |
|:-------------:|:----:|
| 1.793200 | 1 |
| 1.635900 | 2 |
| 1.493000 | 3 |
| 1.227600 | 5 |
| 0.640500 | 10 |
| 0.438300 | 15 |
| 0.370200 | 20 |
| 0.205100 | 30 |
| 0.094900 | 40 |
| 0.068500 | 50 |
| 0.059400 | 60 |
## Licenses
- **License:** apache-2.0 |