/Tools/AI Model Trainer/Docs/Model Evaluation

Model Evaluation

After training, it's important to evaluate your model's performance on unseen data. The AI Model Trainer provides various evaluation metrics and visualizations to help you understand your model's strengths and weaknesses.

Subsections

Evaluation Metrics

The AI Model Trainer provides various evaluation metrics, including accuracy, precision, recall, F1 score, and confusion matrix. These metrics help you understand how well your model is performing on different tasks.

Error Analysis

Understanding where your model makes mistakes is crucial for improving its performance. The AI Model Trainer provides tools for error analysis, allowing you to identify patterns in your model's errors.

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