Phiphi216/medgemma-oncology-lora
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MedGemma Oncology Agent
This repository contains a LoRA fine-tuned oncology agent built on top of MedGemma 1.5 4B IT.
The model is trained to analyze chest CT scan slices together with structured clinical records and predict six-year lung cancer risk.
The model was fine-tuned using Unsloth and PEFT LoRA on a custom oncology dataset.
Model Details
Dataset
Dataset:
- Phiphi216/oncology
Number of samples:
- 2,000 training examples
Each sample contains:
- CT scan identifier
- Patient identifier
- Prompt
- Response
Response format:
{
"lung_cancer_risk": "Cancer within follow-up"
}Training Procedure
Base Model
unsloth/medgemma-1.5-4b-it
LoRA Configuration
r: 16
lora_alpha: 16
lora_dropout: 0.0
finetune_vision_layers: false
finetune_language_layers: true
finetune_attention_modules: true
finetune_mlp_modules: true
optimizer: adamw_torch_fused
learning_rate: 2e-4
weight_decay: 1e-3
lr_scheduler_type: cosine
max_grad_norm: 0.3
per_device_train_batch_size: 2
gradient_accumulation_steps: 2
effective_batch_size: 4
max_seq_length: 25808
max_steps: 125
warmup_ratio: 0