deepspeedai / deepspeedai/DeepSpeedExamples
How can I find bert weights used for ZeroQuant?
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Description
Hi I'm trying to reproduce GLUE scores reported on ZeroQuant paper.
But overally almost every tasks' accuracy is lower than reported results in LKD cases.
Escpecially RTE shows sharp degredation in W4/8A8 LKD case.
I assume diffrent results come out because I am using different checkpoint weights
with those used for the research.
The default setting is to get weights from "yoshitomo-matsubara/bert-base-uncased".
How can I get weights file to reproduce at least similar numbers?
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Research direction
Start at the ZeroQuant GLUE evaluation entry point and inspect the default checkpoint setting for yoshitomo-matsubara/bert-base-uncased. Compare the weights used with those from the ZeroQuant research, then rerun the LKD cases, especially RTE W4/8A8; done means achieving results close to the reported GLUE scores.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
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- Mostly clear
- Newbie friendliness
- 35/100