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CADICA_qwenvl_stenosis_classify_scale4

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 ---
+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-scale4
+  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-scale4
+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scale4(TRAIN) dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1878
+- Num Input Tokens Seen: 39772368
+## 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: 6
+- total_train_batch_size: 24
+- 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: 0.05
+- training_steps: 3400
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss | Input Tokens Seen |
+|:-------------:|:------:|:----:|:---------------:|:-----------------:|
+| 0.9233        | 0.0258 | 50   | 0.9282          | 584856            |
+| 0.9024        | 0.0515 | 100  | 0.9114          | 1169664           |
+| 0.9045        | 0.0773 | 150  | 0.8935          | 1754512           |
+| 0.904         | 0.1030 | 200  | 0.8980          | 2339304           |
+| 0.9106        | 0.1288 | 250  | 0.8958          | 2924016           |
+| 0.8901        | 0.1545 | 300  | 0.8932          | 3508888           |
+| 0.9059        | 0.1803 | 350  | 0.8960          | 4093688           |
+| 0.9033        | 0.2060 | 400  | 0.9063          | 4678384           |
+| 0.9062        | 0.2318 | 450  | 0.9008          | 5263304           |
+| 0.8576        | 0.2575 | 500  | 0.8269          | 5848048           |
+| 0.8666        | 0.2833 | 550  | 0.7910          | 6432936           |
+| 0.7997        | 0.3090 | 600  | 0.7877          | 7017576           |
+| 0.8367        | 0.3348 | 650  | 0.7941          | 7602512           |
+| 0.774         | 0.3605 | 700  | 0.7319          | 8187320           |
+| 0.6751        | 0.3863 | 750  | 0.7322          | 8772104           |
+| 0.6911        | 0.4121 | 800  | 0.7180          | 9357016           |
+| 0.7455        | 0.4378 | 850  | 0.7039          | 9941896           |
+| 0.7378        | 0.4636 | 900  | 0.7198          | 10526712          |
+| 0.6825        | 0.4893 | 950  | 0.6831          | 11111520          |
+| 0.5971        | 0.5151 | 1000 | 0.7079          | 11696200          |
+| 0.6914        | 0.5408 | 1050 | 0.6824          | 12281072          |
+| 0.5825        | 0.5666 | 1100 | 0.6432          | 12865992          |
+| 0.5228        | 0.5923 | 1150 | 0.6230          | 13450720          |
+| 0.5078        | 0.6181 | 1200 | 0.6184          | 14035544          |
+| 0.5268        | 0.6438 | 1250 | 0.5497          | 14620336          |
+| 0.4578        | 0.6696 | 1300 | 0.4947          | 15205064          |
+| 0.4702        | 0.6953 | 1350 | 0.5248          | 15789848          |
+| 0.4294        | 0.7211 | 1400 | 0.4732          | 16374784          |
+| 0.4353        | 0.7468 | 1450 | 0.4350          | 16959632          |
+| 0.3369        | 0.7726 | 1500 | 0.3964          | 17544440          |
+| 0.4666        | 0.7984 | 1550 | 0.4266          | 18129304          |
+| 0.3834        | 0.8241 | 1600 | 0.4477          | 18714072          |
+| 0.475         | 0.8499 | 1650 | 0.3513          | 19298848          |
+| 0.3752        | 0.8756 | 1700 | 0.3438          | 19883504          |
+| 0.3233        | 0.9014 | 1750 | 0.3325          | 20468200          |
+| 0.3279        | 0.9271 | 1800 | 0.3502          | 21053080          |
+| 0.3221        | 0.9529 | 1850 | 0.2935          | 21637848          |
+| 0.3781        | 0.9786 | 1900 | 0.2973          | 22222632          |
+| 0.2845        | 1.0041 | 1950 | 0.2473          | 22801512          |
+| 0.2272        | 1.0299 | 2000 | 0.2834          | 23386232          |
+| 0.2924        | 1.0556 | 2050 | 0.2704          | 23971048          |
+| 0.2805        | 1.0814 | 2100 | 0.3205          | 24555904          |
+| 0.2536        | 1.1071 | 2150 | 0.3081          | 25140752          |
+| 0.3184        | 1.1329 | 2200 | 0.2492          | 25725560          |
+| 0.273         | 1.1586 | 2250 | 0.2201          | 26310336          |
+| 0.2903        | 1.1844 | 2300 | 0.2940          | 26895096          |
+| 0.2757        | 1.2101 | 2350 | 0.2621          | 27479840          |
+| 0.2766        | 1.2359 | 2400 | 0.2361          | 28064552          |
+| 0.3076        | 1.2617 | 2450 | 0.2372          | 28649256          |
+| 0.257         | 1.2874 | 2500 | 0.2489          | 29233968          |
+| 0.2192        | 1.3132 | 2550 | 0.2432          | 29818856          |
+| 0.224         | 1.3389 | 2600 | 0.2026          | 30403640          |
+| 0.2377        | 1.3647 | 2650 | 0.1878          | 30988344          |
+| 0.2269        | 1.3904 | 2700 | 0.2400          | 31573240          |
+| 0.1416        | 1.4162 | 2750 | 0.2472          | 32158144          |
+| 0.2162        | 1.4419 | 2800 | 0.2771          | 32743032          |
+| 0.1912        | 1.4677 | 2850 | 0.2647          | 33327720          |
+| 0.2015        | 1.4934 | 2900 | 0.2392          | 33912440          |
+| 0.2069        | 1.5192 | 2950 | 0.2639          | 34497216          |
+| 0.2027        | 1.5449 | 3000 | 0.2371          | 35082056          |
+| 0.1925        | 1.5707 | 3050 | 0.2484          | 35666976          |
+| 0.2139        | 1.5964 | 3100 | 0.2747          | 36251744          |
+| 0.204         | 1.6222 | 3150 | 0.2423          | 36836560          |
+| 0.1851        | 1.6480 | 3200 | 0.2286          | 37421416          |
+| 0.2072        | 1.6737 | 3250 | 0.2406          | 38006200          |
+| 0.2145        | 1.6995 | 3300 | 0.2692          | 38591128          |
+| 0.2158        | 1.7252 | 3350 | 0.2447          | 39175888          |
+| 0.1488        | 1.7510 | 3400 | 0.2225          | 39760664          |
+### Framework versions
+- PEFT 0.12.0
+- Transformers 4.47.0.dev0
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3