whisper-large-v2-2swissdatasets
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2491
- Wer: 16.5053
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: 5e-06
- train_batch_size: 16
- eval_batch_size: 8
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2827 | 0.0780 | 1000 | 0.3166 | 20.3350 |
| 0.2452 | 0.1560 | 2000 | 0.2901 | 18.7233 |
| 0.2336 | 0.2340 | 3000 | 0.2697 | 17.6650 |
| 0.2519 | 0.3120 | 4000 | 0.2563 | 16.8885 |
| 0.2295 | 0.3900 | 5000 | 0.2491 | 16.5053 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.3.1+cu118
- Datasets 3.2.0
- Tokenizers 0.19.1
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Base model
openai/whisper-large-v2