Whisper Large - Whisper with atcosim_corpus
This model is a fine-tuned version of openai/whisper-large on the The ATCOSIM Air Traffic Control Simulation Speech corpus is a speech database of air traffic control (ATC) operator speech, provided by Graz University of Technology (TUG) and Eurocontrol Experimental Centre (EEC) dataset. It achieves the following results on the evaluation set:
- Loss: 0.0413
- Wer: 0.9496
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 |
|---|---|---|---|---|
| 0.012 | 2.0921 | 1000 | 0.0405 | 1.2543 |
| 0.0019 | 4.1841 | 2000 | 0.0372 | 1.0776 |
| 0.0001 | 6.2762 | 3000 | 0.0407 | 0.9716 |
| 0.0 | 8.3682 | 4000 | 0.0413 | 0.9496 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1