Whisper-ECU 911
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Whisper openai-whisper-large-v3
This model is a fine-tuned version of openai/whisper-large-v3 on the llamadas ecu911 dataset. It achieves the following results on the evaluation set:
- Loss: 1.2300
- Wer: 44.7816
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 |
|---|---|---|---|---|
| 0.3854 | 2.6596 | 500 | 0.7339 | 70.4442 |
| 0.047 | 5.3191 | 1000 | 0.9473 | 48.2910 |
| 0.0096 | 7.9787 | 1500 | 1.1298 | 46.2438 |
| 0.0018 | 10.6383 | 2000 | 1.2300 | 44.7816 |
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-large-v3