Shoriful025/Image_Captioning

Image Captioning Model Overview This vision-language model generates descriptive captions for images using a Vision Transformer encoder and GPT-2 decoder. Fine-tuned on a large dataset of image-caption pairs, it produces natural language descriptions suitable for accessibility tools or content generation. Model Architecture Encoder: Vision Transformer (ViT) with 12 layers, 768 hidden units, and 12 attention heads for image feature extraction. Decoder: GPT-2 with 12 layers for generating captions from encoded features. Intended Use Designed for applications like automated alt-text generation, visual search enhancement, or social media content creation. It processes standard image formats and outputs English captions. Limitations The model may generate inaccurate or biased captions for complex scenes, abstract art, or underrepresented demographics. It performs best on clear, real-world images and might require additional filtering for sensitive content.