When using the Trainer
and TrainingArguments
from transformers, I notice that by default, the Trainer save a model every 500 steps. How can I change this value so that it save the model more/less frequent?
here is a snipet that i use
training_args = TrainingArguments(
output_dir=output_directory, # output directory
num_train_epochs=10, # total number of training epochs
per_device_train_batch_size=16, # batch size per device during training
per_device_eval_batch_size=64, # batch size for evaluation
warmup_steps=500, # number of warmup steps for learning rate scheduler
weight_decay=0.01, # strength of weight decay
logging_dir=log_directory, # directory for storing logs
)
trainer = Trainer(
model=model, # the instantiated 🤗 Transformers model to be trained
args=training_args, # training arguments, defined above
train_dataset=train_dataset, # training dataset
eval_dataset=val_dataset # evaluation dataset
)
trainer.train()