whisper-med-en
This model is a fine-tuned version of openai/whisper-medium.en on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.2607
- eval_wer: 8.3496
- eval_runtime: 2570.8427
- eval_samples_per_second: 3.383
- eval_steps_per_second: 0.423
- epoch: 3.6799
- step: 8000
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: reduce_lr_on_plateau
- lr_scheduler_warmup_steps: 400
- training_steps: 15000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.53.1
- Pytorch 2.5.1+cu124
- Datasets 3.5.1
- Tokenizers 0.21.2
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Base model
openai/whisper-medium.en