Improve model card: Add pipeline tag, library name, tags, and citation

README.md

@@ -1,9 +1,16 @@
 ---
-license: mit
-datasets:
-- TIGER-Lab/ViRL39K
 base_model:
 - Qwen/Qwen2.5-VL-7B-Instruct
+datasets:
+- TIGER-Lab/ViRL39K
+license: mit
+library_name: transformers
+pipeline_tag: video-text-to-text
+tags:
+- lvlm
+- reasoning
+- multimodal
+- qwen
 ---
 
 <p align="center">
@@ -106,7 +113,53 @@ CUDA_VISIBLE_DEVICES=0,1,2,3 vllm serve "$MODEL_PATH" \
 ```
 
 
+## Training
+
+### Spark Training 
+After downloading the dataset, you can start training using the following example bash script. Our bash scripts are in ```/Spark/Lmm_XC/XC/scripts/spark_training```
+You need to modify the dataset paths and model paths to your own locations.
+```
+export WORKSPACE_DIR="/fs-computility/....../Lmm_XC"                 # Path to project root directory
+export DATASET_PATH="/fs-computility/....../infer_data_ViRL_19k.json"            # Path to your dataset
+export PRETRAIN_MODEL_PATH="/fs-computility/....../Qwen2.5-VL-7B-Instruct"  # Path to pretrained model
+export WANDB_PROJECT="Observation"        # Name for this project
+export MODEL_CPK_NAME="Qwen2.5-VL-7B-GRPO-virl-19k-iar-reflection-hyb-diverse-bs64-e2"         # Name for this training run
+export LOG_PATH='/fs-computility/....../Qwen2.5-VL-7B-GRPO-virl-19k-iar-reflection-hyb-diverse-bs64-e2.txt'      #Log file save path
+
+
+export WANDB_API_KEY="......"
+export SAVE_PATH="/fs-computility/....../${WANDB_PROJECT}/${MODEL_CPK_NAME}"                   # Absolute path to save everything about this training run
+export CKPT_PATH="${SAVE_PATH}/ckpt"                                                                    # Path to save checkpoints                                    
+export FINAL_CKPT_PATH="${SAVE_PATH}/final_ckpt"                                                        # Path to save final checkpoints
+export TIMESTAMP=$(date +%Y%m%d_%H%M%S)                                                                 # Timestamp
+export CUR_LOG_DIR="${SAVE_PATH}/training_logs/${TIMESTAMP}"                                            # Path to save current run logs
+export LOG_DIR="${SAVE_PATH}/tb_logs"  
+```
+⏰ Attention:
+```
+export DEV_MODE=0 # Set to 1 for debug mode on single dev machine
+```
+
+## Evaluation
+The integrated multimodal mathematics dataset can be downloaded from 🤗<a href="https://huggingface.co/datasets/internlm/Spark-Data">datasets</a> and evaluated using the scripts provided in the `Evaluation` folder. The evaluation results will be stored, and accuracy can subsequently be computed with the `calculate_acc.py` file.
+```
+bash ./Evaluation/eval_spark_vl_7b.sh
+python calculate_acc.py --result_path ./your_result_path.json
+```
+
 ## ✒️Citation
+```bibtex
+@article{liu2025spark,
+  title={SPARK: Synergistic Policy And Reward Co-Evolving Framework},
+  author={Ziyu Liu and Yuhang Zang and Shengyuan Ding and Yuhang Cao and Xiaoyi Dong and Haodong Duan and Dahua Lin and Jiaqi Wang},
+  journal={arXiv preprint arXiv:2509.22624},
+  year={2025}
+}
 ```
-TBD
-```
+
+## 📄 License
+![Code License](https://img.shields.io/badge/Code%20License-Apache_2.0-green.svg) ![Data License](https://img.shields.io/badge/Data%20License-CC%20By%20NC%204.0-red.svg) **Usage and License Notices**: The data and code are intended and licensed for research use only.
+License: Attribution-NonCommercial 4.0 International It should abide by the policy of OpenAI: https://openai.com/policies/terms-of-use
+
+## Acknowledgement
+We sincerely thank projects <a href="https://github.com/TideDra/lmm-r1">lmm-r1</a> and <a href="https://github.com/OpenRLHF/OpenRLHF">OpenRLHF</a> for providing their open-source resources.