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Whisper Small Ru ORD 0.9 Peft PEFT 4-bit Q DoRA - Mizoru
This model is a fine-tuned version of openai/whisper-small on the ORD_0.9 dataset. It achieves the following results on the evaluation set:
- Loss: 1.1643
- Wer: 58.1771
- Cer: 31.9056
- Clean Wer: 50.6879
- Clean Cer: 26.1504
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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Clean Wer | Clean Cer |
|---|---|---|---|---|---|---|---|
| 1.1675 | 1.0 | 550 | 1.2152 | 60.5918 | 33.7819 | 55.0018 | 28.7141 |
| 1.1217 | 2.0 | 1100 | 1.1698 | 62.6194 | 35.1450 | 54.1401 | 29.5194 |
| 0.9579 | 3.0 | 1650 | 1.1557 | 58.2105 | 32.0513 | 51.0548 | 26.5161 |
| 0.7957 | 4.0 | 2200 | 1.1643 | 58.1771 | 31.9056 | 50.6879 | 26.1504 |
Framework versions
- PEFT 0.11.1.dev0
- Transformers 4.41.0.dev0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.19.1
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