Whisper Small German - GRAG
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the GER-TTS-50-Conversations dataset. It achieves the following results on the evaluation set:
- Loss: 0.4391
- Wer: 15.1703
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|---|---|---|---|---|
| 0.066 | 8.3333 | 1000 | 0.3653 | 15.4640 |
| 0.0038 | 16.6667 | 2000 | 0.4180 | 15.0235 |
| 0.0006 | 25.0 | 3000 | 0.4340 | 15.1882 |
| 0.0004 | 33.3333 | 4000 | 0.4391 | 15.1703 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for MR-Eder/GRAG-whisper-large-v3-turbo-german-v1
Base model
openai/whisper-large-v3
Finetuned
openai/whisper-large-v3-turbo