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add pretrained model and logs
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## Results
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### TedLium3 BPE training results (Zipformer)
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#### 2023-06-15
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Using the codes from this PR https://github.com/k2-fsa/icefall/pull/1125.
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Number of model parameters: 65549011, i.e., 65.5 M
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The WERs are
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| | dev | test | comment |
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|------------------------------------|------------|------------|------------------------------------------|
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| greedy search | 6.74 | 6.16 | --epoch 50, --avg 22, --max-duration 500 |
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| beam search (beam size 4) | 6.56 | 5.95 | --epoch 50, --avg 22, --max-duration 500 |
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| modified beam search (beam size 4) | 6.54 | 6.00 | --epoch 50, --avg 22, --max-duration 500 |
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| fast beam search (set as default) | 6.91 | 6.28 | --epoch 50, --avg 22, --max-duration 500 |
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The training command for reproducing is given below:
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```
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export CUDA_VISIBLE_DEVICES="0,1,2,3"
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./zipformer/train.py \
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--use-fp16 true \
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--world-size 4 \
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--num-epochs 50 \
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--start-epoch 0 \
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--exp-dir zipformer/exp \
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--max-duration 1000
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```
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The tensorboard training log can be found at
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https://tensorboard.dev/experiment/AKXbJha0S9aXyfmuvG4h5A/#scalars
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The decoding command is:
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```
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epoch=50
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avg=22
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## greedy search
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./zipformer/decode.py \
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--epoch $epoch \
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--avg $avg \
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--exp-dir zipformer/exp \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--max-duration 500
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## beam search
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./zipformer/decode.py \
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--epoch $epoch \
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--avg $avg \
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--exp-dir zipformer/exp \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--max-duration 500 \
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--decoding-method beam_search \
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--beam-size 4
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## modified beam search
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./zipformer/decode.py \
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--epoch $epoch \
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--avg $avg \
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--exp-dir zipformer/exp \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--max-duration 500 \
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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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./zipformer/decode.py \
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--epoch $epoch \
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--avg $avg \
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--exp-dir ./zipformer/exp \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--max-duration 1500 \
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--decoding-method fast_beam_search \
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--beam 4 \
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--max-contexts 4 \
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--max-states 8
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```
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A pre-trained model and decoding logs can be found at <https://huggingface.co/desh2608/icefall-asr-tedlium3-zipformer>
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### TedLium3 BPE training results (Conformer-CTC 2)
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#### [conformer_ctc2](./conformer_ctc2)
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@ -722,7 +722,7 @@ def compute_loss(
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is_training: bool,
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) -> Tuple[Tensor, MetricsTracker]:
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"""
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Compute CTC loss given the model and its inputs.
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Compute RNNT loss given the model and its inputs.
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Args:
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params:
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