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Whisper Small English (2000 steps) - Jarrett Er
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.2806
- eval_wer: 13.8607
- eval_runtime: 785.1134
- eval_samples_per_second: 2.547
- eval_steps_per_second: 0.318
- epoch: 0.55
- step: 1100
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
- mixed_precision_training: Native AMP
Framework versions
- PEFT 0.14.0
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.1.dev0
- Tokenizers 0.21.0
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Base model
openai/whisper-small