README.md

metadata

license: apache-2.0
base_model: pinot/wav2vec2-xls-r-300m-ja-phoneme_cv_14_4
tags:
  - generated_from_trainer
datasets:
  - common_voice_13_0
metrics:
  - wer
model-index:
  - name: wav2vec2-xls-r-300m-ja-phoneme-cv_13_test
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_13_0
          type: common_voice_13_0
          config: ja
          split: test
          args: ja
        metrics:
          - name: Wer
            type: wer
            value: 1.0452119589468987

wav2vec2-xls-r-300m-ja-phoneme-cv_13_test

This model is a fine-tuned version of pinot/wav2vec2-xls-r-300m-ja-phoneme_cv_14_4 on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:

• Loss: 3.3902
• Wer: 1.0452

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: 1e-05
• train_batch_size: 8
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.4481	3.22	500	3.3902	1.0452

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu117
• Datasets 2.14.3
• Tokenizers 0.13.3