Whisper Small En 3
This model is a fine-tuned version of openai/whisper-small on the Common Voice 3.0 dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.7635
- eval_wer: 126.2971
- eval_runtime: 2284.865
- eval_samples_per_second: 1.14
- eval_steps_per_second: 0.143
- epoch: 6.68
- step: 5000
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: 8000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
openai/whisper-small