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whisper-medium-1.3
This model is a fine-tuned version of hts98/whisper-medium-1113 on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.2185
- eval_wer: 99.8842
- eval_runtime: 175.2878
- eval_samples_per_second: 4.883
- eval_steps_per_second: 0.411
- epoch: 2.11
- step: 600
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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 1400
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.12.1