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whisper-small-ja
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3967
- Wer: 18.3755
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 200
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
No log | 0.3 | 10 | 1.1627 | 26.0985 |
No log | 0.61 | 20 | 0.7416 | 900.3995 |
1.2431 | 0.91 | 30 | 0.6344 | 60.3196 |
1.2431 | 1.21 | 40 | 0.5944 | 20.2397 |
0.5462 | 1.52 | 50 | 0.5341 | 19.3076 |
0.5462 | 1.82 | 60 | 0.4953 | 18.5087 |
0.5462 | 2.12 | 70 | 0.4715 | 19.9734 |
0.3259 | 2.42 | 80 | 0.4469 | 18.2423 |
0.3259 | 2.73 | 90 | 0.4246 | 19.7071 |
0.1986 | 3.03 | 100 | 0.4076 | 19.0413 |
0.1986 | 3.33 | 110 | 0.3949 | 17.7097 |
0.1986 | 3.64 | 120 | 0.4008 | 20.5060 |
0.1101 | 3.94 | 130 | 0.3892 | 18.3755 |
0.1101 | 4.24 | 140 | 0.3873 | 18.3755 |
0.0695 | 4.55 | 150 | 0.3930 | 19.7071 |
0.0695 | 4.85 | 160 | 0.3857 | 18.1092 |
0.0695 | 5.15 | 170 | 0.3861 | 19.0413 |
0.0467 | 5.45 | 180 | 0.3913 | 18.5087 |
0.0467 | 5.76 | 190 | 0.3963 | 18.7750 |
0.0346 | 6.06 | 200 | 0.3967 | 18.3755 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cpu
- Datasets 2.8.0
- Tokenizers 0.13.2