AI, LLM & Machine Learning Engineering

Model Evaluation & Metrics Calculators

Turning raw counts into the numbers a model is judged on: precision, recall and F1 from a confusion matrix, and perplexity from cross-entropy loss — including the cases where an impressive-looking score means nothing.

3 calculators in this category

F1 Score & Classification Metrics CalculatorF-measure (van Rijsbergen, 1979)Enter the four cells of a confusion matrix and this calculator returns every headline metric a model review asks for…
Confusion Matrix Metrics CalculatorEnter the four cells of a 2×2 confusion matrix and this calculator returns the full metric set, including the three…
Perplexity Calculator (From Cross-Entropy Loss)Shannon entropy (base-e nats, base-2 bits)This calculator converts between the three ways the same quantity gets reported: cross-entropy loss, perplexity, and bits per…

Which one do you need?

F1 Score & Classification Metrics Calculator: Turn a confusion matrix into precision, recall, F1, F-beta, balanced accuracy and the Matthews correlation coefficient, with worked examples.
Confusion Matrix Metrics Calculator: Turn true and false positives and negatives into accuracy, precision, recall, specificity, balanced accuracy, Matthews correlation and Cohen's kappa.
Perplexity Calculator (From Cross-Entropy Loss): Convert cross-entropy loss to perplexity and bits per token, compare against a uniform vocabulary baseline, and translate token perplexity to word level.

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