AutoTrain Model Predictions for Beans Image Classification

A collection of model predictions from the AutoTrain evaluator for a multi-class image classification task. The evaluated model is nateraw/vit-base-beans-demo-v2, and the source dataset is 'beans'. The number of rows, columns, and specific data fields are unknown.

Use Cases

• Compare model predictions against ground truth labels from the 'beans' dataset to assess classification accuracy.
• Analyze prediction confidence scores, if present, to identify challenging image categories within the 'beans' dataset.
• Use the evaluation outputs to benchmark the performance of the nateraw/vit-base-beans-demo-v2 model on the specified task.

Strengths

• Predictions are generated by a specific, named model (nateraw/vit-base-beans-demo-v2) for a defined task (multi-class image classification).
• The source dataset ('beans') is identified, providing context for the evaluation.
• The data was last updated on 2022-06-28.

Limitations

• The dataset's structure is unknown, with no information on rows, columns, or sample data provided.
• The data is from 2022 and may not reflect the current performance of the evaluated model.
• Without access to the original 'beans' dataset labels, the utility of these predictions for analysis is limited.

Provenance

Source

AutoTrain evaluator on Hugging Face.

Collection Method

Model predictions generated by AutoTrain for a specific model evaluation job.

Freshness

Last updated 2022-06-28.