openai/whisper-small
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.26971688866615295
- Wer: 8.508066331024994
Training and evaluation data
- Training data: Myst Train (125 hours)
- Evaluation data: Myst Dev (20.9 hours)
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 64
- eval_batch_size: 32
- 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: 10000
- converged_after: 2500
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Evaluation results
- WER on myst-testtest set self-reported11.800
- WER on cslu_scriptedtest set self-reported55.510
- WER on cslu_spontaneoustest set self-reported28.530
- WER on librispeechself-reported6.230