mT5 fine-tune for en-my got "NaN" in training loss and validation loss

[learnercat]

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I tried to fine-tune mT5 for English->Myanmar translation from Tatoeba-Challenge Dataset. I followed to train this notebook example of en-ro translation. And I used model_checkpoint as "google/mt5-small". I tested 1~4 epoch training. The following is the training parameters, I reduced the batch_size as 4.

batch_size=4 args = Seq2SeqTrainingArguments( "mt5-translate-en-my", evaluation_strategy = "epoch", learning_rate=2e-5, per_device_train_batch_size=batch_size, per_device_eval_batch_size=batch_size, weight_decay=0.01, save_total_limit=3, num_train_epochs=1, predict_with_generate=True, fp16=True, )

I got "NaN" in training loss and validation loss as below:

Can you please help me how do I do it? Thanks in advance.

[msaroufim]

What kind of hardware are you using? Do you get the same issue if you set fp16=False?

[Majdoddin]

@msaroufim Thank you very much, it worked for me on colab. Also the warning lr_schedual.ster() before optimizer.step() disappeared. But why should set fp16=False even when I have A100 GPU on colab?