Comments (5)
It will be added when you run the create_retrieval_data.py
script! Essentially what we did is to select the sentences before the target output sentence y_t
when it makes reflection token predictions!
https://github.com/AkariAsai/self-rag/blob/main/data_creation/generator/create_retrieval_data.py#L89
This discussion might be relevant: #7
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I want to build my own dataset to fine-tune a Critic model, but I found that the prompt in the code has a preceding presence, and I don't know where it comes from and how it was generated?
PROMPT_DICT = { "context": ( "Given an instruction, please make ......TL;DR...... is correct or not.\n" "###\nInstruction: {instruction}\n" "Evidence: {evidence}\n" "Output: {target_output}\n" "Rating: " ) }
I am dealing with the same thing to fine-tune a Critic model. I guess the order in the guideline to run this step
self-rag/data_creation/generator/README.md
Lines 35 to 47 in ed22968
What the author said here is helpful. So I ran the #L35-L47 after doing "Continuous retrieval (t>1)" and before "Create IsRel and IsSUp input data" and got the final constructed data in the correct format.
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当您运行脚本时,它将被添加!从本质上讲,我们所做的是在目标输出句子进行反射标记预测时选择它前面的句子!
create_retrieval_data.py``y_t
https://github.com/AkariAsai/self-rag/blob/main/data_creation/generator/create_retrieval_data.py#L89
这个讨论可能是相关的:#7
But I want to use gpt-4 to build my datasets. What you say is the next setp. So I mean that the 'preceding sentences' from chatgpt_need_retrieval.py
.
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Could you ellaborate your question a bit more? preceding_sentences
will be added if you run the create_retrieval_data.py) script with --multiple_sent
option.
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I am closing this issue for now, but feel free to reopen it!
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Related Issues (20)
- 4 bit quantized version of 7B?
- How long does it takes to train an epoch for critic/generator model on llama-7B with 8 A100?
- What does YOUR_INPUT_FILE look like? Can you provide an example? Thanks very much! HOT 1
- Explanation needed for [Continue to Use Evidence] HOT 1
- How can I get initial input file for generator?
- model issues
- Processed Input Dataset and Flan-3B Critic Generated Dataset
- Reproducing Self-RAG
- accuracy metric HOT 3
- About parameter `max_depth` HOT 2
- Doesn't the generator need to call the retriever when training the model?
- The critic model will generate different type of token when I use run_reward_vllm.py to generate tokens HOT 1
- some problem with run_long_form_static.py
- Data formatting to call the retriever
- Question Regarding Formula Error in Your Paper
- FactScore Inference Fails with KeyError: 'original_splitted_sentences'
- Incorrect setup of Learning Rate Scheduler HOT 6
- dependency HOT 1
- torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: -9) local_rank: 0 (pid: 14447) of binary: HOT 2
- CUDA Memory is not enough
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