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v3-turbo-cv17-telephonic-lora
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the CommonVoice-17_tr_bandpass_filter_telephonic dataset. It achieves the following results on the evaluation set:
- Loss: 0.1411
- Wer: 14.2090
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.454 | 0.1138 | 500 | 0.1633 | 15.3845 |
0.1463 | 0.2276 | 1000 | 0.1525 | 14.9965 |
0.1393 | 0.3414 | 1500 | 0.1482 | 14.7002 |
0.1344 | 0.4552 | 2000 | 0.1466 | 14.4383 |
0.1305 | 0.5690 | 2500 | 0.1442 | 14.3084 |
0.1235 | 0.6828 | 3000 | 0.1427 | 14.2510 |
0.129 | 0.7966 | 3500 | 0.1418 | 14.2434 |
0.1259 | 0.9104 | 4000 | 0.1416 | 14.1765 |
0.1169 | 1.0241 | 4500 | 0.1412 | 14.2185 |
0.1103 | 1.1379 | 5000 | 0.1411 | 14.2090 |
Framework versions
- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0
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Evaluation results
- Wer on CommonVoice-17_tr_bandpass_filter_telephonicself-reported14.209