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The only preprocessing you have to do is to take the argmax of our predicted logits:
import evaluate
metric = evaluate.load("accuracy")
def compute_metrics(eval_pred):
predictions = np.argmax(eval_pred.predictions, axis=1)
return metric.compute(predictions=predictions, references=eval_pred.label_ids)
A note on evaluation:
In the VideoMAE paper, the authors use the following evaluation strategy. |