qwenvl-2B-cadica-stenosis-classify-lora
This model is a fine-tuned version of 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
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Model tree for ben81828/qwenvl-2B-cadica-stenosis-classify-lora
Base model
Qwen/Qwen2-VL-2B
Finetuned
Qwen/Qwen2-VL-2B-Instruct
Finetuned
AdaptLLM/biomed-Qwen2-VL-2B-Instruct