Whisper tiny British
This model is a fine-tuned version of openai/whisper-tiny on the British English 'AE' Phonemes dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.3636
- eval_wer: 13.2631
- eval_runtime: 140.0191
- eval_samples_per_second: 3.392
- eval_steps_per_second: 3.392
- epoch: 2.5
- step: 1500
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: 2
- eval_batch_size: 1
- seed: 42
- optimizer: Use OptimizerNames.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: 500
- training_steps: 2000
Framework versions
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1
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Base model
openai/whisper-tiny