ros/LLaMA-Factory
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Former-commit-id: 7cfede95df22a9ff236788f04159b6b16b8d04bb
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hiyouga
2024-10-29 09:07:46 +00:00
parent 8f5921692e
commit 248d5daaff
66 changed files with 1028 additions and 1044 deletions
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16
src/llamafactory/train/ppo/trainer.py
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@@ -218,18 +218,18 @@ class CustomPPOTrainer(PPOTrainer, Trainer):
if self.is_world_process_zero():
logger.info("***** Running training *****")
logger.info(" Num examples = {:,}".format(num_examples))
logger.info(" Num Epochs = {:,}".format(num_train_epochs))
logger.info(" Instantaneous batch size per device = {:,}".format(self.args.per_device_train_batch_size))
logger.info(f" Num examples = {num_examples:,}")
logger.info(f" Num Epochs = {num_train_epochs:,}")
logger.info(f" Instantaneous batch size per device = {self.args.per_device_train_batch_size:,}")
logger.info(
" Total train batch size (w. parallel, buffer, distributed & accumulation) = {:,}".format(
total_train_batch_size
)
)
logger.info(" Gradient Accumulation steps = {:,}".format(self.args.gradient_accumulation_steps))
logger.info(" Num optimization epochs per batch = {:,}".format(self.finetuning_args.ppo_epochs))
logger.info(" Total training steps = {:,}".format(max_steps))
logger.info(" Number of trainable parameters = {:,}".format(count_parameters(self.model)[0]))
logger.info(f" Gradient Accumulation steps = {self.args.gradient_accumulation_steps:,}")
logger.info(f" Num optimization epochs per batch = {self.finetuning_args.ppo_epochs:,}")
logger.info(f" Total training steps = {max_steps:,}")
logger.info(f" Number of trainable parameters = {count_parameters(self.model)[0]:,}")
dataiter = iter(self.dataloader)
loss_meter = AverageMeter()
@@ -290,7 +290,7 @@ class CustomPPOTrainer(PPOTrainer, Trainer):
if (step + 1) % self.args.save_steps == 0: # save checkpoint
self.save_model(
os.path.join(self.args.output_dir, "{}-{}".format(PREFIX_CHECKPOINT_DIR, self.state.global_step))
os.path.join(self.args.output_dir, f"{PREFIX_CHECKPOINT_DIR}-{self.state.global_step}")
)
self.callback_handler.on_save(self.args, self.state, self.control)