Whisper largeV2 dutch MLS
This model is a fine-tuned version of openai/whisper-large-v2 on the facebook/multilingual_librispeech dutch dataset. It achieves the following results on the evaluation set:
- Loss: 0.2031
- Wer: 10.5916
Model description
The model is fine-tuned for 4000 updates/steps on multilingual librispeech Dutch train data.
- Zero-shot - 9.3 (MLS Dutch test)
- Fine-tune MLS Dutch train - 10.59 (MLS Dutch test)
Even after fine-tuning the model is doing worse than the zero-shot model.
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: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.2515 | 0.25 | 1000 | 0.2579 | 12.9776 |
| 0.24 | 0.5 | 2000 | 0.2361 | 11.2418 |
| 0.1308 | 0.75 | 3000 | 0.2335 | 10.7503 |
| 0.1072 | 1.0 | 4000 | 0.2031 | 10.5916 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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Dataset used to train sgangireddy/whisper-largev2-mls-dutch
Space using sgangireddy/whisper-largev2-mls-dutch 1
Evaluation results
- Wer on facebook/multilingual_librispeech dutchtest set self-reported10.592