Ahmadzei's picture
added 3 more tables for large emb model
5fa1a76
For this task, load the accuracy metric (see the 🤗 Evaluate quick tour to learn more about how to load and compute a metric):
import evaluate
accuracy = evaluate.load("accuracy")
Then create a function that passes your predictions and labels to [~evaluate.EvaluationModule.compute] to calculate the accuracy:
import numpy as np
def compute_metrics(eval_pred):
predictions, labels = eval_pred
predictions = np.argmax(predictions, axis=1)
return accuracy.compute(predictions=predictions, references=labels)
Your compute_metrics function is ready to go now, and you'll return to it when you setup your training.