---
library_name: peft
license: apache-2.0
base_model: AdaptLLM/biomed-Qwen2-VL-2B-Instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: qwenvl-2B-cadica-stenosis-classify-lora
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# qwenvl-2B-cadica-stenosis-classify-lora

This model is a fine-tuned version of [AdaptLLM/biomed-Qwen2-VL-2B-Instruct](https://huggingface.co/AdaptLLM/biomed-Qwen2-VL-2B-Instruct) on the CADICA狹窄分析選擇題(TRAIN) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7947
- Num Input Tokens Seen: 11152104

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 4
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Input Tokens Seen |
|:-------------:|:------:|:----:|:---------------:|:-----------------:|
| 0.9039        | 0.1396 | 50   | 0.9039          | 779728            |
| 0.9033        | 0.2792 | 100  | 0.9009          | 1559632           |
| 0.9001        | 0.4188 | 150  | 0.8988          | 2339368           |
| 0.902         | 0.5585 | 200  | 0.9004          | 3119064           |
| 0.8933        | 0.6981 | 250  | 0.9052          | 3898784           |
| 0.897         | 0.8377 | 300  | 0.9004          | 4678472           |
| 0.8997        | 0.9773 | 350  | 0.9016          | 5458104           |
| 0.9109        | 1.1145 | 400  | 0.8960          | 6224248           |
| 0.8127        | 1.2541 | 450  | 0.8822          | 7003904           |
| 0.8198        | 1.3937 | 500  | 0.8460          | 7783528           |
| 0.832         | 1.5333 | 550  | 0.8188          | 8563264           |
| 0.786         | 1.6729 | 600  | 0.8021          | 9343120           |
| 0.8312        | 1.8126 | 650  | 0.7986          | 10122936          |
| 0.7797        | 1.9522 | 700  | 0.7947          | 10902632          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3