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metadata
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 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