Improve model card and metadata

README.md

@@ -1,208 +1,67 @@
 ---
 base_model: Qwen/Qwen2.5-VL-3B-Instruct
 library_name: peft
-pipeline_tag: text-generation
+pipeline_tag: image-text-to-text
+license: apache-2.0
 tags:
-- base_model:adapter:Qwen/Qwen2.5-VL-3B-Instruct
-- llama-factory
+- finance
 - lora
-- transformers
+- vision-language
+- qwen
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
+# PyFi-QwenVL-3B-47K
 
+This model is a fine-tuned LoRA adapter for [Qwen2.5-VL-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct), specialized for financial image understanding. It was introduced as part of the PyFi framework.
 
 ## Model Details
 
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+- **Developed by:** Yuqun Zhang, Yuxuan Zhao, Sijia Chen (AgenticFinLab)
+- **Model type:** Vision-Language Model (LoRA Adapter)
+- **Base Model:** [Qwen/Qwen2.5-VL-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct)
+- **Language(s):** English
+- **License:** Apache 2.0
+- **Paper:** [PyFi: Toward Pyramid-like Financial Image Understanding for VLMs via Adversarial Agents](https://arxiv.org/abs/2512.14735)
+- **Repository:** [https://github.com/AgenticFinLab/PyFi](https://github.com/AgenticFinLab/PyFi)
 
-[More Information Needed]
+## Summary
 
-### Recommendations
+PyFi (Pyramid-like Financial Image Understanding) is a framework designed to enhance Visual Language Models (VLMs) in understanding complex financial images through adversarial agents. The framework enables VLMs to reason through question chains in a progressive, simple-to-complex manner across six hierarchical capability levels:
+1. **Perception**: Basic visual understanding
+2. **Data Extraction**: Foundational information retrieval
+3. **Calculation Analysis**: Numerical analysis tasks
+4. **Pattern Recognition**: Identifying trends and patterns
+5. **Logical Reasoning**: Complex logical analysis
+6. **Decision Support**: Strategic decision-making assistance
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
+This specific checkpoint was fine-tuned on approximately 47,000 question-answer chains from the **PyFi-600K** dataset. In this version ("w/o CoT"), only the question and answer from the final sample in each chain were used during training to target the ultimate reasoning goal.
 
 ## Training Details
 
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
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-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
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-[More Information Needed]
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-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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-[More Information Needed]
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-#### Metrics
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-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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-[More Information Needed]
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-### Results
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-[More Information Needed]
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-#### Summary
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-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
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-[More Information Needed]
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-#### Hardware
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-[More Information Needed]
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-#### Software
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-[More Information Needed]
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-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
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-[More Information Needed]
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-**APA:**
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-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
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-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
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-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
-### Framework versions
-
-- PEFT 0.17.1
+The model was fine-tuned with the following configuration:
+- **Optimizer**: AdamW
+- **Learning Rate**: $1.0 \times 10^{-4}$
+- **Learning Rate Schedule**: Cosine scheduling with warmup ratio of 0.1
+- **Training Epochs**: 1
+- **Batch Size**: Effective batch size of 8
+- **PEFT**: LoRA with full-module adaptation
+- **Hardware**: 4x NVIDIA RTX 5090 GPUs
+
+## Citation
+
+If you use PyFi in your research, please cite:
+
+```bibtex
+@article{pyfi2025,
+  title={PyFi: Toward Pyramid-like Financial Image Understanding for VLMs via Adversarial Agents},
+  author={Zhang, Yuqun and Zhao, Yuxuan and Chen, Sijia},
+  journal={arXiv preprint arXiv:2512.14735},
+  year={2025}
+}
+```
+
+## Contact
+
+For questions or inquiries, please contact:
+- **Email**: Yuqun Zhang ([research@yuqunzhang.com](mailto:research@yuqunzhang.com)) or Yuxuan Zhao ([yx.zhao129@gmail.com](mailto:yx.zhao129@gmail.com))
+- **GitHub Issues**: [https://github.com/AgenticFinLab/PyFi/issues](https://github.com/AgenticFinLab/PyFi/issues)