# Low Accuracy Model

An audio classification model fine-tuned on the minds14 dataset based on facebook/wav2vec2-base

A fine-tuned speech classification model based on facebook/wav2vec2-base for audio folder dataset classification tasks

A video analysis model fine-tuned on the UCF-Crime dataset based on the VideoMAE foundation model

This is an image classification model generated based on HuggingPics, specifically designed to recognize various top products of the Adidas brand.

An indoor scene classification model based on YOLOv8, used for recognizing and classifying various indoor scenes.

An image classification model generated by HuggingPics for identifying specific categories of images

A speech recognition model fine-tuned on the minds14 dataset based on facebook/wav2vec2-base

An image classification model generated by HuggingPics for recognizing specific categories of images

This model is a fine-tuned Spanish sentiment analysis model based on glob-asr/xls-r-es-test-lm, achieving an accuracy of 23.85% on the evaluation set.

This is an image classification model automatically generated by HuggingPics, specifically designed to identify different types of Goan-style fried fish.

This model is a fine-tuned text classification model based on the distilroberta-base architecture, trained on the julien-c/reactiongif dataset, primarily used for reaction GIF classification tasks.