Automatic Speech Recognition
NeMo
PyTorch
4 languages
automatic-speech-translation
speech
audio
Transformer
FastConformer
Conformer
NeMo
hf-asr-leaderboard
Eval Results
krishnacpuvvada steveheh commited on
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Update README.md (#7)

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- Update README.md (f97bbd620972efd5f2c4d22652c2bbde29cd7746)


Co-authored-by: He Huang <steveheh@users.noreply.huggingface.co>

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README.md CHANGED
@@ -402,7 +402,7 @@ The model outputs the transcribed/translated text corresponding to the input aud
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  ## Training
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  Canary-1B is trained using the NVIDIA NeMo toolkit [4] for 150k steps with dynamic bucketing and a batch duration of 360s per GPU on 128 NVIDIA A100 80GB GPUs.
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- The model can be trained using this [example script](https://github.com/NVIDIA/NeMo/blob/canary-2/examples/asr/speech_multitask/speech_to_text_aed.py) and [base config](https://github.com/NVIDIA/NeMo/blob/canary-2/examples/asr/conf/speech_multitask/fast-conformer_aed.yaml).
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  The tokenizers for these models were built using the text transcripts of the train set with this [script](https://github.com/NVIDIA/NeMo/blob/main/scripts/tokenizers/process_asr_text_tokenizer.py).
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  ## Training
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  Canary-1B is trained using the NVIDIA NeMo toolkit [4] for 150k steps with dynamic bucketing and a batch duration of 360s per GPU on 128 NVIDIA A100 80GB GPUs.
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+ The model can be trained using this [example script](https://github.com/NVIDIA/NeMo/blob/main/examples/asr/speech_multitask/speech_to_text_aed.py) and [base config](https://github.com/NVIDIA/NeMo/blob/main/examples/asr/conf/speech_multitask/fast-conformer_aed.yaml).
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  The tokenizers for these models were built using the text transcripts of the train set with this [script](https://github.com/NVIDIA/NeMo/blob/main/scripts/tokenizers/process_asr_text_tokenizer.py).
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