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whisper-small_child50K_timeStretch_stepLR
This model is a fine-tuned version of openai/whisper-small on the child-50k dataset. It achieves the following results on the evaluation set:
- Loss: 0.0201
- Wer: 2.1061
- Cer: 0.8189
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: 1.25e-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
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
0.1004 | 0.18 | 500 | 0.0796 | 9.5440 | 4.0921 |
0.0846 | 0.36 | 1000 | 0.0453 | 5.3319 | 2.3843 |
0.0729 | 0.53 | 1500 | 0.0355 | 4.2849 | 1.7311 |
0.0486 | 0.71 | 2000 | 0.0284 | 2.8701 | 1.2241 |
0.045 | 0.89 | 2500 | 0.0261 | 3.6220 | 2.6581 |
0.0206 | 1.07 | 3000 | 0.0207 | 2.0616 | 0.8263 |
0.0264 | 1.24 | 3500 | 0.0219 | 2.0091 | 0.8275 |
0.0304 | 1.42 | 4000 | 0.0205 | 1.7827 | 0.7207 |
0.0224 | 1.6 | 4500 | 0.0233 | 2.3527 | 0.9527 |
0.0215 | 1.78 | 5000 | 0.0201 | 2.1061 | 0.8189 |
Framework versions
- Transformers 4.34.1
- Pytorch 1.12.1
- Datasets 2.14.5
- Tokenizers 0.14.1