update ppo trainer
This commit is contained in:
@@ -39,11 +39,12 @@ def run_ppo(
|
||||
reward_model = create_reward_model(model, model_args, finetuning_args)
|
||||
|
||||
# Create ppo config
|
||||
backward_batch_size = training_args.per_device_train_batch_size * training_args.gradient_accumulation_steps
|
||||
ppo_config = PPOConfig(
|
||||
model_name=model_args.model_name_or_path,
|
||||
learning_rate=training_args.learning_rate,
|
||||
mini_batch_size=training_args.per_device_train_batch_size,
|
||||
batch_size=training_args.per_device_train_batch_size * training_args.gradient_accumulation_steps,
|
||||
batch_size=backward_batch_size * finetuning_args.ppo_buffer_size,
|
||||
gradient_accumulation_steps=training_args.gradient_accumulation_steps,
|
||||
ppo_epochs=finetuning_args.ppo_epochs,
|
||||
max_grad_norm=training_args.max_grad_norm,
|
||||
@@ -62,9 +63,7 @@ def run_ppo(
|
||||
if training_args.max_steps > 0:
|
||||
num_training_steps = training_args.max_steps
|
||||
else:
|
||||
total_train_batch_size = (
|
||||
training_args.per_device_train_batch_size * training_args.gradient_accumulation_steps * training_args.world_size
|
||||
)
|
||||
total_train_batch_size = backward_batch_size * finetuning_args.ppo_buffer_size * training_args.world_size
|
||||
num_training_steps = training_args.num_train_epochs * math.ceil(len(dataset) / total_train_batch_size)
|
||||
|
||||
lr_scheduler = get_scheduler(
|
||||
|
||||
Reference in New Issue
Block a user