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The link of the model weights is now unavailable. #9

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BeachWang opened this issue Feb 5, 2024 · 4 comments
Open

The link of the model weights is now unavailable. #9

BeachWang opened this issue Feb 5, 2024 · 4 comments

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@BeachWang
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BeachWang commented Feb 5, 2024

Hi,

I try to reproduce your work with the reported codes. The loss in pretrain and finetune meets expectations. But I get ridiculous answer in eval. For example:

Q:
Is there a snowboard in the image?
Answer the question using a single word or phrase.

A:
50

So can you upload the model weights to help me debug.
Thank you very much!

@clarencerat
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Yeah model weights are not available . Authors of repo please release it , i am excited to see.
Screenshot from 2024-02-06 10-57-19

@BeachWang
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BeachWang commented Feb 6, 2024

I find the link to huggingface is available. But I test it on MME and only get 1110.96 score.
截屏2024-02-06 下午2 10 28

@BeachWang
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Hi,

I try to reproduce your work with the reported codes. The loss in pretrain and finetune meets expectations. But I get ridiculous answer in eval. For example:

Q: Is there a snowboard in the image? Answer the question using a single word or phrase.

A: 50

So can you upload the model weights to help me debug. Thank you very much!

The bug may be in the preprocess_v0 in train.py. It should be

# instruction_len = len(tokenizer(parts[0]).input_ids)
instruction_len = len(tokenizer(parts[0]).input_ids) - 1

, since the last space will be tokenized in parts[0] but be tokenized with other contents in target.

@yhcao6
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yhcao6 commented Mar 22, 2024

Hi,
I try to reproduce your work with the reported codes. The loss in pretrain and finetune meets expectations. But I get ridiculous answer in eval. For example:
Q: Is there a snowboard in the image? Answer the question using a single word or phrase.
A: 50
So can you upload the model weights to help me debug. Thank you very much!

The bug may be in the preprocess_v0 in train.py. It should be

# instruction_len = len(tokenizer(parts[0]).input_ids)
instruction_len = len(tokenizer(parts[0]).input_ids) - 1

, since the last space will be tokenized in parts[0] but be tokenized with other contents in target.

I also got 1110.96 on MME, have you fixed the performance sir?

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3 participants