Update README.md

README.md

@@ -1,60 +1,25 @@
 ---
-library_name: transformers
-license: other
-base_model: Qwen/Qwen2.5-VL-7B-Instruct
-tags:
-- llama-factory
-- full
-- generated_from_trainer
-model-index:
-- name: ViLaSR-cold-start
-  results: []
+datasets:
+- AntResearchNLP/ViLaSR-data
+language:
+- en
+base_model:
+- Qwen/Qwen2.5-VL-7B-Instruct
 ---
 
-<!-- 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. -->
 
-# ViLaSR-cold-start
+This repository contains the ViLaSR-cold-start-7B model as presented in [Reinforcing Spatial Reasoning in Vision-Language Models with Interwoven Thinking and Visual Drawing](https://arxiv.org/abs/2506.09965).
 
-This model is a fine-tuned version of [Qwen/Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct) on the vqa_v4, the video_v4, the spatial_r1_v5_0, the spatial_r1_v5_1 and the maze datasets.
+Please refer to the code https://github.com/AntResearchNLP/ViLaSR.
 
-## 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: 1e-05
-- train_batch_size: 1
-- eval_batch_size: 8
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 64
-- total_train_batch_size: 64
-- total_eval_batch_size: 512
-- 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: 3.0
-
-### Training results
-
-
-
-### Framework versions
-
-- Transformers 4.51.1
-- Pytorch 2.5.1
-- Datasets 3.5.0
-- Tokenizers 0.21.0
+```
+@misc{wu2025reinforcingspatialreasoningvisionlanguage,
+      title={Reinforcing Spatial Reasoning in Vision-Language Models with Interwoven Thinking and Visual Drawing}, 
+      author={Junfei Wu and Jian Guan and Kaituo Feng and Qiang Liu and Shu Wu and Liang Wang and Wei Wu and Tieniu Tan},
+      year={2025},
+      eprint={2506.09965},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2506.09965}, 
+}
+```