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Whisper Large Ru ORD 0.9 Peft PEFT 4-bit Q DoRA - Mizoru
This model is a fine-tuned version of openai/whisper-large-v2 on the ORD_0.9 dataset. It achieves the following results on the evaluation set:
- Loss: 2.8845
- Wer: 74.8477
- Cer: 38.7512
- Clean Wer: 36.9662
- Clean Cer: 22.6459
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 |
|---|---|---|---|---|---|---|---|
| 0.4253 | 1.0 | 500 | 2.7477 | 74.1292 | 39.0216 | 37.6289 | 23.1469 |
| 0.3839 | 2.0 | 1000 | 3.0590 | 74.9874 | 39.2363 | 38.2604 | 23.1286 |
| 0.3321 | 3.0 | 1500 | 2.8845 | 74.8477 | 38.7512 | 36.9662 | 22.6459 |
Framework versions
- PEFT 0.12.0
- Transformers 4.41.0.dev0
- Pytorch 2.3.1
- Datasets 3.2.0
- Tokenizers 0.19.1
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openai/whisper-large-v2