| license: apache-2.0 | |
| language: | |
| - en | |
| pipeline_tag: image-to-text | |
| library_name: transformers | |
| base_model: Qwen/Qwen-VL | |
| tags: | |
| - vision-language | |
| - chart-understanding | |
| - chart-question-answering | |
| - document-understanding | |
| - multimodal | |
| datasets: | |
| - custom | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: ChartQwen | |
| results: [] | |
| # ChartQwen | |
| ## Model Description | |
| ChartQwen is a vision-language model fine-tuned from **Qwen/Qwen-VL** for chart understanding tasks. | |
| The model is designed to interpret visual charts such as bar charts, line graphs, and plots, and answer natural language questions related to them. | |
| It supports multimodal reasoning by jointly processing images and text prompts. | |
| --- | |
| ## Intended Use | |
| This model can be used for: | |
| - Chart question answering | |
| - Chart data interpretation | |
| - Visual reasoning over plots and graphs | |
| - Document and report analysis involving charts | |
| --- | |
| ## Training Details | |
| - **Base model:** Qwen/Qwen-VL | |
| - **Modality:** Image + Text | |
| - **Fine-tuning type:** Supervised fine-tuning on chart-related visual-question pairs | |
| - **Dataset:** Custom chart dataset (generated and curated for chart understanding) | |
| ## Limitations | |
| - Performance may degrade on low-resolution or highly cluttered charts | |
| - The model may struggle with handwritten charts or uncommon chart styles | |
| - Numerical precision depends on chart clarity | |
| --- |