Update README.md

README.md

@@ -126,11 +126,6 @@ answer = response.split("<|im_start|>assistant")[-1].strip()
 print(answer)
 ```
 
-## Training Details
-
-### Training Data
-
-The model was fine-tuned on multimodal vision-language data including Chinese, Korean, and English content, with specific focus on Traditional Chinese Medicine tongue diagnosis scenarios.
 
 ### Training Procedure
 
@@ -147,35 +142,6 @@ The model was fine-tuned on multimodal vision-language data including Chinese, K
 - **Adapter size:** 2.2GB
 - **Base model:** Qwen2.5-VL-32B-Instruct (32B parameters)
 
-## Evaluation
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-Evaluation was performed on multimodal vision-language benchmarks with focus on medical image understanding and TCM tongue diagnosis.
-
-#### Metrics
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-Standard vision-language evaluation metrics including accuracy, BLEU, and human evaluation scores.
-
-### Results
-
-[Evaluation results to be added]
-
-#### Summary
-
-This LoRA adapter provides an efficient way to adapt the Qwen2.5-VL-32B-Instruct model for Traditional Chinese Medicine tongue diagnosis tasks while maintaining the base model's capabilities.
-
-## Technical Specifications
-
-### Model Architecture and Objective
-
-- **Architecture:** LoRA adapter for Qwen2.5-VL-32B-Instruct
-- **Objective:** Multimodal vision-language understanding and generation, specialized for TCM tongue diagnosis
-
-### Compute Infrastructure
-
 
 #### Software