IoanaLiviaPopescu/real-data-whisper-small-without-normalize-eval
This model is a fine-tuned version of openai/whisper-small on the IoanaLiviaPopescu/RealVoiceHoroscope dataset. It achieves the following results on the evaluation set:
- Loss: 0.4132
- Wer: 26.8763
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0 | 0 | 0.6024 | 35.6728 |
| 0.501 | 1.0 | 13 | 0.4965 | 28.2987 |
| 0.3039 | 2.0 | 26 | 0.4347 | 28.6356 |
| 0.1973 | 3.0 | 39 | 0.4132 | 26.8763 |
| 0.1431 | 4.0 | 52 | 0.4076 | 26.9699 |
| 0.1181 | 5.0 | 65 | 0.4097 | 27.1196 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1