# Moderate Accuracy

An audio classification model fine-tuned based on facebook/wav2vec2-base, achieving 58.92% accuracy on the evaluation set

This is a multi-class image classification model trained via AutoTrain, specifically designed for dementia-related image classification tasks.

This is a medical image classification model based on the ViT architecture, specifically designed for breast composition analysis, fine-tuned on the preprocessed 1024 configuration dataset.

This model is a vision model based on the Vision Transformer (ViT) architecture, focusing on the classification task of algae images.

A facial expression recognition model fine-tuned based on the ResNet-50 architecture, trained on the FER2013 dataset with an accuracy of 68.47%

A weather image classification model based on ResNet architecture for identifying images under different weather conditions

A five-class image classifier for identifying orcs and their companions (goblins, sprites, ogres, trolls)

A speech processing model fine-tuned based on facebook/wav2vec2-base, achieving an accuracy of 53.57% on the evaluation set