Ddp #32
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Ddp #32
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ddlBoJack
reviewed
Jan 25, 2024
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| train_config: | ||
| model_name: "PATH/to/LLAMA/7B" | ||
| enable_fsdp: false |
ddlBoJack
reviewed
Jan 25, 2024
| ++train_config.lr=1e-4 \ | ||
| ++train_config.output_dir=$output_dir \ | ||
| ++train_config.peft_config.peft_method=lora \ | ||
| ++metric=acc \ |
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metric to be classified to a certain class
ddlBoJack
reviewed
Jan 25, 2024
| ++train_config.enable_fsdp=true \ | ||
| ++train_config.enable_ddp=false \ | ||
| ++train_config.use_fp16=true \ | ||
| ++metric=acc \ |
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metric to be classified to a certain class
ddlBoJack
reviewed
Jan 25, 2024
| use_fp16: false | ||
| # sharding_strategy: "FULL_SHARD" #ShardingStrategy = ShardingStrategy.FULL_SHARD | ||
| sharding_strategy: "NO_SHARD" #ShardingStrategy.NO_SHARD #MZY: set NO_SHARD to use DDP mode in FSDP | ||
| checkpoint_type: "StateDictType.SHARDED_STATE_DICT" # alternatively can use SHARDED_STATE_DICT save one file per rank, and can resize the world-size. |
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To unify with only the str name, say, "SHARDED_STATE_DICT"
ddlBoJack
reviewed
Jan 25, 2024
| @@ -229,12 +233,12 @@ def train(model, train_dataloader,eval_dataloader, tokenizer, optimizer, lr_sche | |||
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| else: | |||
| if not train_config.use_peft and fsdp_config.checkpoint_type == StateDictType.FULL_STATE_DICT: | |||
| if not train_config.use_peft and fsdp_config.checkpoint_type == "StateDictType.FULL_STATE_DICT": | |||
ddlBoJack
reviewed
Jan 25, 2024
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| save_model_checkpoint( | ||
| model, optimizer, rank, train_config, epoch=epoch | ||
| ) | ||
| elif not train_config.use_peft and fsdp_config.checkpoint_type == StateDictType.SHARDED_STATE_DICT: | ||
| elif not train_config.use_peft and fsdp_config.checkpoint_type == "StateDictType.SHARDED_STATE_DICT": |
ddlBoJack
approved these changes
Jan 25, 2024
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What does this PR do?
Fixes # (issue)
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