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Hyperparameter of the number of distractor documents and the ratio of golden documents in training RAFT #325

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yifan1130 opened this issue Apr 7, 2024 · 1 comment · Fixed by #353

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@yifan1130
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Hi, I just wonder what the number of distractor documents and the ratio of golden documents in training RAFT are in producing the results in the paper. I saw the default ratio in the script the ratio is 1.0, which means no distractor documents are used. I wonder whether the default number in the scripts represents the hyperparameter used to produce the results in the paper?

@kaiwen129
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Hi, the optimal value for the P% hyperparameter may vary from dataset to dataset. To answer your question, the paper used various values of P%, not just the default value of 1.0 in the script.

ShishirPatil added a commit that referenced this issue Apr 14, 2024
Change `p` which dictates the fraction of dataset with golden documents
in them (vs) no golden documents.

So, p = 0.8 means, for 80% of the train data set, `A* = Q + D* + D1 ..
Dn` and for 20% of the train data set `A* = Q + D1 .. Dn` where `D*`
are/is the golden document with the answer `A*`.

Close #325
devanshamin pushed a commit to devanshamin/gorilla that referenced this issue Jul 9, 2024
Change `p` which dictates the fraction of dataset with golden documents
in them (vs) no golden documents.

So, p = 0.8 means, for 80% of the train data set, `A* = Q + D* + D1 ..
Dn` and for 20% of the train data set `A* = Q + D1 .. Dn` where `D*`
are/is the golden document with the answer `A*`.

Close ShishirPatil#325
aw632 pushed a commit to vinaybagade/gorilla that referenced this issue Aug 22, 2024
Change `p` which dictates the fraction of dataset with golden documents
in them (vs) no golden documents.

So, p = 0.8 means, for 80% of the train data set, `A* = Q + D* + D1 ..
Dn` and for 20% of the train data set `A* = Q + D1 .. Dn` where `D*`
are/is the golden document with the answer `A*`.

Close ShishirPatil#325
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2 participants