Whisper Large V3 Turbo FT TR Telephonic - Alperitoo
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1739
- Wer: 15.6307
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: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1657 | 0.6154 | 1000 | 0.2519 | 21.1461 |
0.0993 | 1.2308 | 2000 | 0.2193 | 19.6685 |
0.0838 | 1.8462 | 3000 | 0.2031 | 18.6612 |
0.0574 | 2.4615 | 4000 | 0.1923 | 16.5399 |
0.0247 | 3.0769 | 5000 | 0.1739 | 15.6307 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0
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Model tree for Alperitoo/whisper-v3-turbo-common
Base model
openai/whisper-large-v3
Finetuned
openai/whisper-large-v3-turbo
Dataset used to train Alperitoo/whisper-v3-turbo-common
Evaluation results
- Wer on Common Voice 11.0validation set self-reported15.631