Whisper Small Japanese
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 ja dataset. It achieves the following results on the evaluation set:
- Loss: 0.3617
- Wer: 68.9459
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1938 | 1.09 | 1000 | 0.2841 | 74.6631 |
0.0466 | 3.06 | 2000 | 0.2996 | 72.0953 |
0.005 | 5.04 | 3000 | 0.3376 | 70.4355 |
0.0021 | 7.01 | 4000 | 0.3617 | 68.9459 |
0.002 | 8.1 | 5000 | 0.3735 | 71.4711 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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Dataset used to train jakeyoo/whisper-small-ja
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 jatest set self-reported68.946