Model Predictions for Multi-Class Image Classification on Snacks Dataset

Encompassing model predictions generated by AutoTrain for a multi-class image classification task. The predictions are for the 'Matthijs/snacks' dataset using the 'matteopilotto/vit-base-patch16-224-in21k-snacks' model. The specific number of rows, columns, and sample data are unknown.

Use Cases

• Analyze model prediction outputs for the 'Matthijs/snacks' dataset to assess classification performance.
• Compare AutoTrain-generated predictions against ground truth labels for the multi-class image classification task.
• Use the model predictions to identify potential misclassifications or challenging categories within the snacks dataset.

Strengths

• Predictions generated by the AutoTrain platform, a known automated evaluation tool.
• Associated with a specific model ('matteopilotto/vit-base-patch16-224-in21k-snacks') and dataset ('Matthijs/snacks').
• Dataset was last updated on 2022-06-27.

Limitations

• The dataset's size, structure, and specific column schema are unknown, limiting usability.
• Data is from 2022, which may be stale for evaluating current model performance.
• Lacks ground truth labels or original images, requiring the user to source the base 'snacks' dataset for meaningful analysis.

Provenance

Source

AutoTrain Evaluator (autoevaluate) on Hugging Face.

Collection Method

Model predictions generated by the AutoTrain platform for an evaluation job.

Freshness

Last updated 2022-06-27; update frequency unknown.

Geography

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