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README.md

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+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.