I've follow some of the post I found online by setting the .to('cpu')
method
model = AutoModelForMaskedLM.from_pretrained(MODEL_TYPE).to('cpu')
Then in the training argument: I've set the number of device to 8 (total CPU on the device) and set the no_cuda=True
training_args = TrainingArguments(
output_dir=output_dir,
overwrite_output_dir=True,
evaluation_strategy="steps",
learning_rate=2e-5,
weight_decay=0.01,
logging_steps = 10,
save_total_limit=5,
load_best_model_at_end=True,
gradient_accumulation_steps=2,
per_device_train_batch_size=8,
prediction_loss_only=True,
remove_unused_columns=False,
no_cuda=True
)
The code starts executing and the HF progress bar appears as expected.
But when I check the task manager CPU usage hover around 50%, while using Chrome in the meantime, so it's clearly not taking advantage of all CPU available but I don't know what I'm missing.