Classifies a photograph of a place as water (a river, lake, ocean, waterfall, pond, canal or fountain is visibly identifiable) or nowater. Built for the 24-679 neural-network AutoML homework to practise budgeted architecture / hyperparameter search with early stopping, leakage-safe validation, and model documentation. It is trained on 23 original photographs and is a classroom demonstration, not a production water detector. prepared by a classmate for Homework 1: 34 original iPhone photos from their camera roll, largest-square-cropped and LANCZOS-resized to 224×224 RGB, labelled by the dataset author (17 water / 17 no-water originals). copies (391 rows); validation = 5 original photos; test…
Independent publisher
Feng Xiong
shanexf
Models in Library2
Datasets in Library0
Models on Hugging Face4
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Published tasks: Image classification, Text classification.
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Models
A prompting pipeline (no weights were trained) that classifies short garment descriptions into top, bottom, outerwear, dress, footwear with a local instruction-tuned LLM. Three pipelines are compared: zero-shot, adaptive one-shot and adaptive K-shot (K = 5), plus random-selection ablations. Built for the 24-679 multi-shot prompting homework as the comparison point for the fine-tuned DistilBERT model on the same data. - leixiang25/24679-hw1-text-garments (commit 49d58b5a09420224a7d4d00fd983b9febd260f8f): fictional garment descriptions written by a classmate; no license assigned by the dataset card, no personal data or brands. Validation: 15 originals, used to check prompt settings. Test: 15…