Comments (2)
Thank you very much for your interest!
In the paper, we claim that IFD is ineffective for code data because there is so little code-related data that has a relatively high IFD score. So I think if you specifically want code-related data, you can increase the number of code data chosen. For example, directly calculating the IFD scores on code cluster to ensure the number of code data.
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Thank you very much for your interest! In the paper, we claim that IFD is ineffective for code data because there is so little code-related data that has a relatively high IFD score. So I think if you specifically want code-related data, you can increase the number of code data chosen. For example, directly calculating the IFD scores on code cluster to ensure the number of code data.
Thank you for your reply. Following your suggestion, my understanding is to train a initial model using a subset of code data separately, and then evaluate the IFD value of the full code data.
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Related Issues (19)
- Need help: the loss curve is strange. HOT 3
- Questions related to training HOT 5
- Could the Pre-Experienced Model be used in other different dataset? HOT 1
- Any report of time consuming? HOT 1
- Chinese SFT data cannot be displayed. HOT 3
- 'The training of pre-experienced models is discarded for more efficient usage': that means we can only use base model to do cherry analysis and selection? HOT 1
- batch? HOT 1
- 关于Direct Answer Score sθ(A) HOT 2
- Evaluation reproducibility on benchmarks HOT 4
- how many epochs to train on cherry data? HOT 2
- a confusion about Instruction-Following Difficulty (IFD) scores HOT 2
- a confusion about data_by_IFD HOT 3
- Logic behind IFD score HOT 1
- I plan to apply this method on Llama2, which part of this project needs to be changed to adapt to Llama2? HOT 1
- May I ask if this project is suitable for other large models, such as the Baichuan model, to filter high-quality datasets from other fields HOT 4
- about the paper HOT 1
- Multi-round conversation data set HOT 3
- GPT-4/ChatGPT Evaluation Code HOT 1
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