BanglaMedVQA: Bengali Medical Visual Question Answering Training Data

A dataset for fine-tuning the MedGemma-4B vision-language model for Bengali medical question answering. The repository contains training and testing configurations for models like Qwen2.5-VL-7B and MedGemma-4B. It was created by iiCEMAN and last updated on April 8, 2026.

Use Cases

• Fine-tuning vision-language models for Bengali medical question answering based on the described training configurations.
• Testing multimodal model performance on a Bengali medical domain based on the provided testing configurations.
• Developing specialized medical AI assistants for Bengali-speaking populations based on the described fine-tuning approach.

Strengths

• Targets a low-resource language (Bengali) in the medical AI domain.
• Includes specific training configurations for models like MedGemma-4B and Qwen2.5-VL-7B.
• Repository structure is documented with separate configs for training and testing.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file formats, and sample data are unknown, which may limit suitability assessment.

Provenance

Source

huggingface

Collection Method

Likely created for fine-tuning a vision-language model using LoRA.

Time Range

null

Freshness

Last updated 2026-04-08 08:35:26; freshness should be verified.

Geography

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