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# Results
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### IWSLT Tunisian training results (Stateless Pruned Transducer)
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#### 2023-06-01
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| Decoding method | dev WER | test WER | comment |
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|------------------------------------|------------|------------|------------------------------------------|
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| modified beam search | 47.6 | 51.2 | --epoch 20, --avg 10 |
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| modified beam search | 47.6 | 51.2 | --epoch 20, --avg 13 |
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The training command for reproducing is given below:
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#### 2023-06-01
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You can find a pretrained model, training logs, decoding logs, and decoding results at:
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https://tensorboard.dev/experiment/yLE399ZPTzePG8B39jRyOw/
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<https://huggingface.co/AmirHussein/zipformer-iwslt22-Ta>
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| Decoding method | dev WER | test WER | comment |
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|------------------------------------|------------|------------|------------------------------------------|
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| modified beam search | 40.8 | 44.4 | --epoch 20, --avg 10 |
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| modified beam search | 40.8 | 44.1 | --epoch 20, --avg 13 |
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To reproduce the above result, use the following commands for training:
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@ -70,7 +71,7 @@ To reproduce the above result, use the following commands for training:
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```
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export CUDA_VISIBLE_DEVICES="0,1"
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./zipformer/train.py \
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--world-size 2 \
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--world-size 4 \
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--num-epochs 20 \
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--start-epoch 1 \
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--use-fp16 1 \
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--num-encoder-layers 2,2,2,2,2,2 \
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--feedforward-dim 512,768,1024,1536,1024,768 \
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--encoder-dim 192,256,384,512,384,256 \
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--encoder-unmasked-dim 192,192,256,256,256,192
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--encoder-unmasked-dim 192,192,256,256,256,192 \
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--use-averaged-model true
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done
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```
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#### 2023-06-01
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You can find a pretrained model, training logs, decoding logs, and decoding results at:
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<https://huggingface.co/AmirHussein/zipformer-iwslt22-Ta>
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@ -95,8 +96,6 @@ To reproduce the above result, use the following commands for training:
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```
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The tensorboard training log can be found at
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https://tensorboard.dev/experiment/4sa4M1mRQyKjOE4o95mWUw/
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The decoding command is:
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