speech to text
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Speech to text models
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Updated
breeze-listen-dsw-small-ml
This model is a fine-tuned version of openai/whisper-small on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3647
- Wer: 34.3837
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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4577 | 1.02 | 100 | 0.4824 | 58.3874 |
| 0.1781 | 2.04 | 200 | 0.3066 | 41.0658 |
| 0.0935 | 3.06 | 300 | 0.2903 | 35.6441 |
| 0.057 | 5.0 | 400 | 0.3289 | 36.6172 |
| 0.0285 | 6.03 | 500 | 0.3425 | 35.3197 |
| 0.0203 | 7.05 | 600 | 0.3647 | 34.3837 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
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Model tree for simpragma/breeze-listen-dsw-small-ml
Base model
openai/whisper-small