Whisper Small En - Whisper with ATCOSIM
This model is a fine-tuned version of openai/whisper-small on the Air Traffic Control Simulation Speech corpus dataset. It achieves the following results on the evaluation set:
- Loss: 0.0487
- Wer: 1.4442
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0014 | 2.09 | 1000 | 0.0482 | 1.5944 |
| 0.0001 | 4.18 | 2000 | 0.0491 | 1.5944 |
| 0.0 | 6.28 | 3000 | 0.0480 | 1.4266 |
| 0.0 | 8.37 | 4000 | 0.0487 | 1.4442 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2