Whisper-ECU 911
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Whisper openai-whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the llamadas ecu911 dataset. It achieves the following results on the evaluation set:
- Loss: 1.3073
- Wer: 43.7154
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: 2
- eval_batch_size: 1
- 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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4916 | 2.6596 | 500 | 0.8382 | 43.4866 |
| 0.0412 | 5.3191 | 1000 | 1.0742 | 44.0397 |
| 0.0078 | 7.9787 | 1500 | 1.2294 | 44.1160 |
| 0.0011 | 10.6383 | 2000 | 1.3073 | 43.7154 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
openai/whisper-medium