swap optimizer.step and scheduler.step
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@@ -602,8 +602,8 @@ def main():
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nb_tr_examples += input_ids.size(0)
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nb_tr_steps += 1
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if (step + 1) % args.gradient_accumulation_steps == 0:
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scheduler.step() # Update learning rate schedule
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optimizer.step()
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scheduler.step() # Update learning rate schedule
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optimizer.zero_grad()
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global_step += 1
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