
The results:

|Vocab size | Greedy search(dev & test) | Modified beam search(dev & test) | Fast beam search (dev & test)  | Fast beam search LG (dev & test) | comments|
|-- | -- | -- | -- | -- | --|
|500 | 4.31 & 4.59 | 4.25 & 4.54 | 4.27 & 4.55 |  4.07 & 4.38 | --epoch 48 --avg 29|



The training command:


```bash
export CUDA_VISIBLE_DEVICES="4,5,6,7"

./pruned_transducer_stateless7_bbpe/train.py \
  --world-size 4 \
  --num-epochs 50 \
  --start-epoch 1 \
  --use-fp16 1 \
  --max-duration 800 \
  --bpe-model data/lang_bbpe_500/bbpe.model \
  --exp-dir pruned_transducer_stateless7_bbpe/exp \
  --lr-epochs 6 \
  --master-port 12535
```


The decoding command:


```bash
for m in greedy_search modified_beam_search fast_beam_search fast_beam_search_LG; do 
    ./pruned_transducer_stateless7_bbpe/decode.py \                                                                                                                                                                                              
      --epoch 48 \                                                                                                                                                                                                                         
      --avg 29 \                                                                                                                                                                                                                           
      --exp-dir ./pruned_transducer_stateless7_bbpe/exp \                                                                                                                                                                                  
      --max-sym-per-frame 1 \                                                                                                                                                                                                              
      --ngram-lm-scale 0.25 \                                                                                                                                                                                                            
      --ilme-scale 0.2 \                                                                                                                                                                                                                 
      --bpe-model data/lang_bbpe_500/bbpe.model \                                                                                                                                                                                         
      --max-duration 2000 \                                                                                                                                                                                                                
      --decoding-method $m
done
```

{"license": "apache-2.0"}
tensorboard license:apache-2.0 region:us
TAGS
#tensorboard #license-apache-2.0 #region-us 

The results:



The training command:


The decoding command:



TAGS
#tensorboard #license-apache-2.0 #region-us 
