tensorboard region:us
## Results

### Aishell training results (Fine-tuning Pretrained Models)
#### Whisper

##### fine-tuning results on Aishell test set on whisper medium, large-v2, large-v3

|                        | test (greedy search, before fine-tuning) | test (beam=10, after fine-tuning)  | comment                                 |
|------------------------|------|------|-----------------------------------------|
| medium         | 7.23 | 3.27 | --epoch 10 --avg 4,  ddp                         |
| large-v2       | 6.56 | 2.47 | --epoch 10 --avg 6,  deepspeed zero stage1       |
| large-v3       | 6.06 | 2.84 | --epoch 5 --avg 3,   deepspeed zero stage1       |

Command for training is:
```bash
./prepare.sh --stage 30 --stop_stage 30

#fine-tuning with deepspeed zero stage 1
torchrun --nproc-per-node 8 ./whisper/train.py \
  --max-duration 200 \
  --use-fp16 1 \
  --exp-dir whisper/exp_large_v2 \
  --model-name large-v2 \
  --deepspeed \
  --deepspeed_config ./whisper/ds_config_zero1.json

# fine-tuning with ddp
torchrun --nproc-per-node 8 ./whisper/train.py \
  --max-duration 200 \
  --use-fp16 1 \
  --exp-dir whisper/exp_medium \
  --base-lr 1e-5 \
  --model-name medium
```

Command for decoding is:
```bash
python3 ./whisper/decode.py \
  --exp-dir whisper/exp_large_v2 \
  --model-name large-v2 \
  --epoch 999 --avg 1 \
  --beam-size 10 --max-duration 50
```
NOTE: To decode with original whisper models, you should pad the input features into 30 secs. Otherwise it may not ouput EOS token.

Pretrained models, training logs, decoding logs, tensorboard and decoding results
are available at
<https://huggingface.co/yuekai/icefall_asr_aishell_whisper>