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update wandb monitor

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This commit is contained in:
gongjy 2024-09-23 22:16:21 +08:00
parent 235b6c6fd3
commit 7947fa17fb
3 changed files with 3 additions and 3 deletions
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2
1-pretrain.py
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@ -74,7 +74,7 @@ def train_epoch(epoch, wandb, accumulation_steps=8):
optimizer.param_groups[-1]['lr'], optimizer.param_groups[-1]['lr'],
spend_time / (step + 1) * iter_per_epoch // 60 - spend_time // 60)) spend_time / (step + 1) * iter_per_epoch // 60 - spend_time // 60))
if (use_wandb is not None) and (not ddp or dist.get_rank() == 0): if (wandb is not None) and (not ddp or dist.get_rank() == 0):
wandb.log({"loss": loss.item() * accumulation_steps, wandb.log({"loss": loss.item() * accumulation_steps,
"lr": optimizer.param_groups[-1]['lr'], "lr": optimizer.param_groups[-1]['lr'],
"epoch_Time": spend_time / (step + 1) * iter_per_epoch // 60 - spend_time // 60}) "epoch_Time": spend_time / (step + 1) * iter_per_epoch // 60 - spend_time // 60})

2
3-full_sft.py
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@ -86,7 +86,7 @@ def train_epoch(epoch, wandb):
optimizer.param_groups[-1]['lr'], optimizer.param_groups[-1]['lr'],
spend_time / (step + 1) * iter_per_epoch // 60 - spend_time // 60)) spend_time / (step + 1) * iter_per_epoch // 60 - spend_time // 60))
if (use_wandb is not None) and (not ddp or dist.get_rank() == 0): if (wandb is not None) and (not ddp or dist.get_rank() == 0):
wandb.log({"loss": loss, wandb.log({"loss": loss,
"lr": optimizer.param_groups[-1]['lr'], "lr": optimizer.param_groups[-1]['lr'],
"epoch_Time": spend_time / (step + 1) * iter_per_epoch // 60 - spend_time // 60}) "epoch_Time": spend_time / (step + 1) * iter_per_epoch // 60 - spend_time // 60})

2
4-lora_sft.py
View File

@ -73,7 +73,7 @@ def train_epoch(epoch, wandb):
optimizer.param_groups[-1]['lr'], optimizer.param_groups[-1]['lr'],
spend_time / (step + 1) * iter_per_epoch // 60 - spend_time // 60)) spend_time / (step + 1) * iter_per_epoch // 60 - spend_time // 60))
if use_wandb is not None: if wandb is not None:
wandb.log({"loss": loss.item(), "lr": optimizer.param_groups[-1]['lr'], wandb.log({"loss": loss.item(), "lr": optimizer.param_groups[-1]['lr'],
"epoch_Time": spend_time / (step + 1) * iter_per_epoch // 60 - spend_time // 60}) "epoch_Time": spend_time / (step + 1) * iter_per_epoch // 60 - spend_time // 60})