mlcommons / mlcommons/algorithmic-efficiency
librispeech deepspeech validation loss differs between pytorch and jax, but wer aligns
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- Dominant language
- Python
- Stars
- 425
- Forks
- 78
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Description
Provide a general description of the issue
validation loss:
wer:
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no files, tests, or entry points and provides only validation-loss and WER screenshots. Start by locating the LibriSpeech DeepSpeech implementations for PyTorch and JAX, then compare their validation-loss calculations and inputs. Done means the discrepancy is explained or corrected while the aligned WER behavior is preserved.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 38/100