Whisper Medium CGN
This model is a fine-tuned version of openai/whisper-medium on the kul-speech-lab/CGN dataset. It achieves the following results on the evaluation set:
- Loss: 0.2639
- Wer: 10.7278
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 64
- eval_batch_size: 32
- 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: 15000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1116 | 1.01 | 1000 | 0.2978 | 15.2127 |
| 0.0786 | 2.03 | 2000 | 0.2842 | 13.4852 |
| 0.2042 | 3.04 | 3000 | 0.2656 | 13.3590 |
| 0.1183 | 4.05 | 4000 | 0.2667 | 12.6977 |
| 0.0584 | 6.01 | 5000 | 0.2604 | 12.0993 |
| 0.0126 | 7.02 | 6000 | 0.2776 | 12.1477 |
| 0.0837 | 8.04 | 7000 | 0.2541 | 11.9397 |
| 0.0229 | 9.05 | 8000 | 0.2663 | 11.3221 |
| 0.042 | 11.01 | 9000 | 0.2549 | 11.4863 |
| 0.0075 | 12.02 | 10000 | 0.2775 | 11.0780 |
| 0.008 | 13.03 | 11000 | 0.2499 | 10.9759 |
| 0.0739 | 14.05 | 12000 | 0.2308 | 10.9441 |
| 0.0379 | 16.01 | 13000 | 0.2423 | 10.7926 |
| 0.02 | 17.02 | 14000 | 0.2629 | 10.7699 |
| 0.0111 | 18.03 | 15000 | 0.2639 | 10.7278 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
Whisper medium model finetuned on Flemish part of Corpus Gesproken Nederlands (CGN).
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