Whisper Base myPin
This model is a fine-tuned version of openai/whisper-base on the Domain Based voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.0769
- Wer: 34.5238
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use 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: 100
- training_steps: 1500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2114 | 36.3636 | 500 | 0.2534 | 100.0 |
| 0.0186 | 72.7273 | 1000 | 0.0846 | 36.3095 |
| 0.0067 | 109.0909 | 1500 | 0.0769 | 34.5238 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
openai/whisper-base