File size: 2,741 Bytes
01f03fd cffcbbd 01f03fd cffcbbd 01f03fd cffcbbd 01f03fd |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 |
---
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 |