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waxal-omniasr-ctc-1b-multilingual – AI Model by Paulownia | AlphaNeural AI
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Paulownia
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waxal-omniasr-ctc-1b-multilingual
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fairseq2
automatic-speech-recognition
apache-2.0
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Model trained from Meta OmniASR CTC 1B on the three languages.
Training result
Best checkpoint: step 5000
Speaker-held-out internal WER: 24.6375%
Internal validation CTC loss: 46.6428
Training: 5,000 optimizer steps on an NVIDIA A100 80GB
Data: 29,308 training utterances / 164.28 hours
Held-out development: 4,655 utterances / 24.64 hours, speaker-disjoint from training
The internal WER above is a development diagnostic. See artifacts/validation_history.csv and artifacts/training_summary.json for the full trajectory.
Files
best/final/model.pt: final best inference weights
best/model.yaml: fairseq2 model metadata
resume/step_5000/: complete model, optimizer, trainer, and data-reader resume state
config/ctc-1b-full.yaml: reproducible training configuration
artifacts/: validation history, raw safe metric JSONL, summary, and evaluator guard patch
