Hugging Face Text Classification — Fine-Tuned Custom Model

Built food vs not-food binary text classification model using PyTorch and Hugging Face Transformers, Datasets, Tokenizers, Evaluate, and Accelerate. Created custom caption dataset, configured AutoModelForSequenceClassification and TrainingArguments, trained with Trainer API, evaluated performance, and published interactive Gradio demo on Hugging Face Spaces. Demonstrates transfer learning and end-to-end NLP pipeline ownership.

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