Swin Model Predictions on Food101 Image Classification

Comprising model predictions generated by AutoTrain for a multi-class image classification task. The evaluated model is skylord/swin-finetuned-food101 on the Food101 dataset. The specific number of rows, columns, and data size are unknown.

Use Cases

• Analyze model prediction outputs from skylord/swin-finetuned-food101 for error patterns in Food101 image classification.
• Benchmark the performance of the swin-finetuned-food101 model against other models using its prediction data.
• Use the AutoTrain-generated predictions to study classification confidence scores for the Food101 categories.

Strengths

• Predictions generated by the AutoTrain platform, a known automated evaluation tool.
• Associated with the established Food101 dataset for image classification.
• Data is tagged with relevant metadata including modality (image) and region (us).

Limitations

• The dataset's size, row count, column structure, and sample data are completely unknown.
• The data is from 2022 and may not reflect the current performance of the evaluated model.
• Lack of column definitions prevents understanding of the specific prediction metrics available.

Provenance

Source

Hugging Face AutoTrain Evaluator (autoevaluate).

Collection Method

Model predictions generated automatically by the AutoTrain platform for evaluation.

Freshness

Last updated on 2022-06-28.

Geography

Region tag indicates 'us', but specific spatial coverage is unknown.