def compute_metrics()

in src/utils.py [0:0]

• 17 lines of code
• 1 McCabe index (conditional complexity)

def compute_metrics(p):
    logits, labels = p
    predictions = np.argmax(logits, axis=1)
    # Combine metrics
    accuracy_metric = evaluate.load("accuracy")
    precision_metric = evaluate.load("precision")
    recall_metric = evaluate.load("recall")
    f1_metric = evaluate.load("f1")

    # Calculate metrics
    accuracy = accuracy_metric.compute(predictions=predictions, references=labels)
    precision = precision_metric.compute(predictions=predictions, references=labels, average="weighted")
    recall = recall_metric.compute(predictions=predictions, references=labels, average="weighted")
    f1 = f1_metric.compute(predictions=predictions, references=labels, average="weighted")

    return {
        "accuracy": accuracy["accuracy"],
        "precision": precision["precision"],
        "recall": recall["recall"],
        "f1": f1["f1"]
    }