Whisper Base Japanese Elite
This model is a fine-tuned version of openai/whisper-base on the Elite35P-Server/EliteVoiceProject twitter dataset. It achieves the following results on the evaluation set:
- Loss: 0.4385
- Wer: 17.0732
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 200
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0002 | 111.0 | 1000 | 0.2155 | 9.7561 |
0.0001 | 222.0 | 2000 | 0.2448 | 12.1951 |
0.0 | 333.0 | 3000 | 0.2674 | 13.4146 |
0.0 | 444.0 | 4000 | 0.2943 | 15.8537 |
0.0 | 555.0 | 5000 | 0.3182 | 17.0732 |
0.0 | 666.0 | 6000 | 0.3501 | 18.9024 |
0.0 | 777.0 | 7000 | 0.3732 | 16.4634 |
0.0 | 888.0 | 8000 | 0.4025 | 17.0732 |
0.0 | 999.0 | 9000 | 0.4178 | 20.1220 |
0.0 | 1111.0 | 10000 | 0.4385 | 17.0732 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2
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Dataset used to train noflm/whisper-base-ja-elite
Evaluation results
- Wer on Elite35P-Server/EliteVoiceProject twittertest set self-reported17.073