---
tags:
- generated_from_trainer
datasets:
- null
model-index:
- name: wav2vec2-live-japanese
  results:
  - {}
---


---
language: ja
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: wav2vec2-live-japanese
  results:
  - task:
      name: Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice Japanese
      type: common_voice
      args: ja
    metrics:
       - name: Test WER
         type: wer
         value: 22.08%
       - name: Test CER
         type: cer
         value: 10.08%
---

# wav2vec2-live-japanese

https://github.com/ttop32/wav2vec2-live-japanese-translator
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Japanese using the 
- common_voice
- JSUT
- CSS10
- TEDxJP-10K
- JVS

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 3
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 6
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 50
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.10.0
- Pytorch 1.9.1
- Datasets 1.11.0
- Tokenizers 0.10.3