Comments (2)
gaotianyu1350
commented on May 17, 2024
Hi, thanks for your interest in our work!
About automatic search, template search starts from manual label words, and label word search starts from manual templates. In either method, we need to start from something manual.
About GPU cards, we always use one card. If you are running it on a multi-GPU machine and only want to use one card, you should set CUDA_VISIBLE_DEVICES to the desired card ID.
We have mentioned in our paper that we found automatic template (+ manual label words) works better than automatic label words, so we follow this method in our final LM-BFF. So yes to your last question.
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LeeSureman
commented on May 17, 2024
哇，感谢你的及时回复！太棒了
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Related Issues (20)
- Question about prompt-based finetuning and automatic selection of label words HOT 3
- Negative CoLA MCC - Prompt-Based Finetuning error? HOT 2
- Bug in dataloader ? HOT 3
- Table 3 uses manual label words or generated label words? HOT 2
- Average the logits of 16 demonstrations HOT 1
- label generation problem HOT 2
- num_k parameter is not used HOT 4
- Bug in tools/ensemble.py/get_labels HOT 2
- A little question about the evaluation HOT 1
- lm_bff.json文件中相互关联的参数："inspired_templates", "replace_token_map_list"如何设置？ HOT 1
- Bug in get_sbert_embedding.py? HOT 2
- The issue for the loss of regression tasks HOT 1
- question about label words which consist of more than 2 sub tokens HOT 1
- Weird SST2 dataset size HOT 4
- Hyperparameter selection for Finetuning Full setting. HOT 1
- How can I create templates for right to left languages?
- Some questions regarding details of your paper results HOT 2
- Problem with the requirements file HOT 1
- cannot import name 'default_hp_search_backend' from 'transformers.integrations' HOT 4
- Adapting LM-BFF to WiC dataset
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