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@ -244,6 +244,87 @@ for m in greedy_search modified_beam_search fast_beam_search; do
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done
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done
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```
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```
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### pruned_transducer_stateless7 (Fine-tune with mux)
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See <https://github.com/k2-fsa/icefall/pull/1059> for more details.
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[pruned_transducer_stateless7](./pruned_transducer_stateless7)
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The tensorboard log can be found at
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<https://tensorboard.dev/experiment/MaNDZfO7RzW2Czzf3R2ZRA/>
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You can find the pretrained model and bpe model needed for fine-tuning at:
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<https://huggingface.co/csukuangfj/icefall-asr-librispeech-pruned-transducer-stateless7-2022-11-11>
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You can find a fine-tuned model, fine-tuning logs, decoding logs, and decoding
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results at:
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<https://huggingface.co/yfyeung/icefall-asr-finetune-mux-pruned_transducer_stateless7-2023-05-19>
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You can use <https://github.com/k2-fsa/sherpa> to deploy it.
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Number of model parameters: 70369391, i.e., 70.37 M
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| decoding method | dev | test | test-clean | test-other | comment |
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|----------------------|------------|------------|------------|------------|--------------------|
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| greedy_search | 14.27 | 14.22 | 2.08 | 4.79 | --epoch 20 --avg 5 |
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| modified_beam_search | 14.22 | 14.08 | 2.06 | 4.72 | --epoch 20 --avg 5 |
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| fast_beam_search | 14.23 | 14.17 | 2.08 | 4.09 | --epoch 20 --avg 5 |
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The training commands are:
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```bash
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export CUDA_VISIBLE_DEVICES="0,1"
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./pruned_transducer_stateless7/finetune.py \
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--world-size 2 \
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--num-epochs 20 \
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--start-epoch 1 \
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--exp-dir pruned_transducer_stateless7/exp_giga_finetune \
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--subset S \
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--use-fp16 1 \
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--base-lr 0.005 \
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--lr-epochs 100 \
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--lr-batches 100000 \
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--bpe-model icefall-asr-librispeech-pruned-transducer-stateless7-2022-11-11/data/lang_bpe_500/bpe.model \
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--do-finetune True \
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--use-mux True \
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--finetune-ckpt icefall-asr-librispeech-pruned-transducer-stateless7-2022-11-11/exp/pretrain.pt \
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--max-duration 500
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```
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The decoding commands are:
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```bash
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# greedy_search
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./pruned_transducer_stateless7/decode.py \
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--epoch 20 \
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--avg 5 \
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--use-averaged-model 1 \
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--exp-dir ./pruned_transducer_stateless7/exp_giga_finetune \
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--max-duration 600 \
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--decoding-method greedy_search
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# modified_beam_search
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./pruned_transducer_stateless7/decode.py \
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--epoch 20 \
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--avg 5 \
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--use-averaged-model 1 \
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--exp-dir ./pruned_transducer_stateless7/exp_giga_finetune \
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--max-duration 600 \
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--decoding-method modified_beam_search \
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--beam-size 4
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# fast_beam_search
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./pruned_transducer_stateless7/decode.py \
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--epoch 20 \
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--avg 5 \
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--use-averaged-model 1 \
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--exp-dir ./pruned_transducer_stateless7/exp_giga_finetune \
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--max-duration 600 \
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--decoding-method fast_beam_search \
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--beam 20.0 \
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--max-contexts 8 \
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--max-states 64
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```
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### pruned_transducer_stateless7 (zipformer + multidataset(LibriSpeech + GigaSpeech + CommonVoice 13.0))
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### pruned_transducer_stateless7 (zipformer + multidataset(LibriSpeech + GigaSpeech + CommonVoice 13.0))
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See <https://github.com/k2-fsa/icefall/pull/1010> for more details.
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See <https://github.com/k2-fsa/icefall/pull/1010> for more details.
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