Whisper Medium 2hr
This model is a fine-tuned version of openai/whisper-medium on the Radio dataset dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.4054
- eval_wer: 15.0273
- eval_runtime: 415.198
- eval_samples_per_second: 2.317
- eval_steps_per_second: 0.291
- epoch: 13.11
- step: 800
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-06
- 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: 1600
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
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