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45 lines
1.3 KiB
Markdown
45 lines
1.3 KiB
Markdown
## Results
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### Zh-En datasets bpe-based training results (Non-streaming) on Zipformer model
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This is the [pull request #1238](https://github.com/k2-fsa/icefall/pull/1265) in icefall.
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#### Non-streaming (Byte-Level BPE vocab_size=2000)
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Best results (num of params : ~69M):
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The training command:
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```
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./zipformer/train.py \
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--world-size 4 \
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--num-epochs 35 \
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--use-fp16 1 \
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--max-duration 1000 \
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--num-workers 8
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```
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The decoding command:
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```
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for method in greedy_search modified_beam_search fast_beam_search; do
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./zipformer/decode.py \
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--epoch 34 \
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--avg 19 \
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--decoding_method $method
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done
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```
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Word Error Rates (WERs) listed below are produced by the checkpoint of the 20th epoch using greedy search and BPE model (# tokens is 2000).
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| Datasets | TAL-CSASR | TAL-CSASR |
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|----------------------|-----------|-----------|
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| Zipformer WER (%) | dev | test |
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| greedy_search | 6.65 | 6.69 |
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| modified_beam_search | 6.46 | 6.51 |
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| fast_beam_search | 6.57 | 6.68 |
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Pre-trained model can be found here : https://huggingface.co/zrjin/icefall-asr-zipformer-multi-zh-en-2023-11-22, which is trained on LibriSpeech 960-hour training set (with speed perturbation), TAL-CSASR training set (with speed perturbation) and AiShell-2 (w/o speed perturbation).
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