[chat] Fix coati-sft-Instruction Tuning

[NicholasCao]

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1. Fix coati-sft-Instruction Tuning (applications/Chat/coati/dataset/sft_dataset.py)

• Multiple unnecessary copy.deepcopy leads to slow tokenizer
• Use tokenizer.eos_token instead of the fixed <|endoftext|>
• Fix input_ids
• Fix wrong attribute name self.prompts
• Fix NameError: name 'data_collator' is not defined (applications/Chat/examples/train_sft.py line 114)

2. Fix: log when is_rank_0 (applications/Chat/coati/trainer/sft.py)

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[Fazziekey]

@NicholasCao good work, thanks a lot for your contribution

[allaccs]

Hello, I trained a model yesterday without those changes. What are the consequences of these?
Is the tokenizer wrong in the old code? Where the self.input_ids wrong?

[NicholasCao]

@allaccs If your args.dataset != 'yizhongw/self_instruct', there are no errors.
Otherwise, make sure the tokenizer you use satisfies tokenizer.eos_token == '<|endoftext|>'.
The rest are some efficiency or redundancy issues that do not cause any errors.

[Fazziekey]

@allaccs如果您的args.dataset != 'yizhongw/self_instruct'，则没有错误。 否则，请确保您使用的分词器满足 tokenizer.eos_token == '<|endoftext|>'. 剩下的就是一些不会导致任何错误的效率或者冗余问题。

acctually, 'yizhongw/self_instruct' is a community contirbutred, and we put it here tempory, and we will remove it to community exampple