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Add ckp_dir and tokenizer path

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xunuohope1107 2025-02-18 16:36:29 +08:00 committed by GitHub
parent 844e79148c
commit 44f30197ac
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1 changed files with 4 additions and 2 deletions
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train_full_sft.py
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@ -96,10 +96,10 @@ def train_epoch(epoch, wandb):
def init_model(lm_config): def init_model(lm_config):
tokenizer = AutoTokenizer.from_pretrained('./model/minimind_tokenizer') tokenizer = AutoTokenizer.from_pretrained(args.tokenizer_path)
model = MiniMindLM(lm_config) model = MiniMindLM(lm_config)
moe_path = '_moe' if lm_config.use_moe else '' moe_path = '_moe' if lm_config.use_moe else ''
ckp = f'./out/pretrain_{lm_config.dim}{moe_path}.pth' ckp = f'{args.ckp_dir}/pretrain_{lm_config.dim}{moe_path}.pth'
state_dict = torch.load(ckp, map_location=args.device) state_dict = torch.load(ckp, map_location=args.device)
model.load_state_dict(state_dict, strict=False) model.load_state_dict(state_dict, strict=False)
Logger(f'LLM总参数量：{sum(p.numel() for p in model.parameters() if p.requires_grad) / 1e6:.3f} 百万') Logger(f'LLM总参数量：{sum(p.numel() for p in model.parameters() if p.requires_grad) / 1e6:.3f} 百万')
@ -122,6 +122,8 @@ def init_distributed_mode():
if __name__ == "__main__": if __name__ == "__main__":
parser = argparse.ArgumentParser(description="MiniMind Full SFT") parser = argparse.ArgumentParser(description="MiniMind Full SFT")
parser.add_argument("--out_dir", type=str, default="out") parser.add_argument("--out_dir", type=str, default="out")
parser.add_argument("--ckp_dir", type=str, default="out", help="Directory to save/load checkpoints")
parser.add_argument("--tokenizer_path", type=str, default="./model/minimind_tokenizer", help="Path to the tokenizer")
parser.add_argument("--epochs", type=int, default=1) parser.add_argument("--epochs", type=int, default=1)
parser.add_argument("--batch_size", type=int, default=32) parser.add_argument("--batch_size", type=int, default=32)
parser.add_argument("--learning_rate", type=float, default=5e-5) parser.add_argument("--learning_rate", type=float, default=5e-5)