LoRA adapter for HuggingFaceTB/SmolVLM2-2.2B-Instruct, fine-tuned for Bengali Visual Question Answering on the Bangla-Bayanno dataset.

Trained on a single Colab T4 GPU (16GB) with a constrained time/step budget (LoRA r=16, False QLoRA, fp16, image-splitting disabled for speed).

Per-answer-type breakdown (BanglaVLM-v1):

Caveats: Trained on a ~7,000-example subset (not the full 42k+ train split) for ~1,000 optimizer steps to fit Colab's free-tier time/session limits. Descriptive-answer accuracy remains low; do not extrapolate beyond these measured numbers.