Comments (2)
ChangwenXu98
commented on June 8, 2024
Hi @liberty-1776, thanks for raising the issue. Your suggestion is valuable, and we've updated the code. Meanwhile, even though the square brackets are included, the effect is just having a '[' after the start token '' and a ']' before the end token '', so we believe that the performance of the pretrained model will be almost the same after removing the square brackets. And the downstream performance should be the same as the results we report in paper (if not better) since the tokens from the downstream sequences do not have such issue.
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liberty-1776
commented on June 8, 2024
Yeah, that's right
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Related Issues (13)
- Finetuning attention maps HOT 5
- Issues with the running of Downsteam.py HOT 1
- Question about Tokenizer HOT 2
- OSError: Can't load tokenizer for 'roberta-base'. HOT 1
- RuntimeError: Error(s) in loading state_dict for DownstreamRegression: HOT 1
- Finetuned model HOT 3
- Different block_size for pretrain and finetune HOT 3
- Cloning Issue HOT 1
- Regarding Validation Error and Testing Error HOT 1
- Regarding Egc Dataset HOT 2
- Supplementary Vocab File HOT 4
- TypeError when using Downstream.py HOT 4
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