Improve model card: Add pipeline tag, library name, tags, and citation (#1)
Browse files- Improve model card: Add pipeline tag, library name, tags, and citation (2aa1ff1ac1b0f714c39077e3d3d56099f9ae8b3e)
Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>
README.md
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---
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license: mit
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datasets:
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- TIGER-Lab/ViRL39K
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base_model:
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- Qwen/Qwen2.5-VL-7B-Instruct
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---
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<p align="center">
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```
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## ✒️Citation
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```
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---
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base_model:
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- Qwen/Qwen2.5-VL-7B-Instruct
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datasets:
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- TIGER-Lab/ViRL39K
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license: mit
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library_name: transformers
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pipeline_tag: video-text-to-text
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tags:
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- lvlm
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- reasoning
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- multimodal
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- qwen
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<p align="center">
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```
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## Training
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### Spark Training
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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```
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You need to modify the dataset paths and model paths to your own locations.
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```
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export WORKSPACE_DIR="/fs-computility/....../Lmm_XC" # Path to project root directory
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export DATASET_PATH="/fs-computility/....../infer_data_ViRL_19k.json" # Path to your dataset
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export PRETRAIN_MODEL_PATH="/fs-computility/....../Qwen2.5-VL-7B-Instruct" # Path to pretrained model
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export WANDB_PROJECT="Observation" # Name for this project
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export MODEL_CPK_NAME="Qwen2.5-VL-7B-GRPO-virl-19k-iar-reflection-hyb-diverse-bs64-e2" # Name for this training run
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export LOG_PATH='/fs-computility/....../Qwen2.5-VL-7B-GRPO-virl-19k-iar-reflection-hyb-diverse-bs64-e2.txt' #Log file save path
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export WANDB_API_KEY="......"
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export SAVE_PATH="/fs-computility/....../${WANDB_PROJECT}/${MODEL_CPK_NAME}" # Absolute path to save everything about this training run
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export CKPT_PATH="${SAVE_PATH}/ckpt" # Path to save checkpoints
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export FINAL_CKPT_PATH="${SAVE_PATH}/final_ckpt" # Path to save final checkpoints
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export TIMESTAMP=$(date +%Y%m%d_%H%M%S) # Timestamp
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export CUR_LOG_DIR="${SAVE_PATH}/training_logs/${TIMESTAMP}" # Path to save current run logs
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export LOG_DIR="${SAVE_PATH}/tb_logs"
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```
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⏰ Attention:
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```
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export DEV_MODE=0 # Set to 1 for debug mode on single dev machine
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```
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## Evaluation
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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.
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```
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bash ./Evaluation/eval_spark_vl_7b.sh
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python calculate_acc.py --result_path ./your_result_path.json
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```
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## ✒️Citation
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```bibtex
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@article{liu2025spark,
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title={SPARK: Synergistic Policy And Reward Co-Evolving Framework},
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author={Ziyu Liu and Yuhang Zang and Shengyuan Ding and Yuhang Cao and Xiaoyi Dong and Haodong Duan and Dahua Lin and Jiaqi Wang},
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journal={arXiv preprint arXiv:2509.22624},
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year={2025}
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}
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```
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## 📄 License
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  **Usage and License Notices**: The data and code are intended and licensed for research use only.
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License: Attribution-NonCommercial 4.0 International It should abide by the policy of OpenAI: https://openai.com/policies/terms-of-use
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## Acknowledgement
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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.
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