whisper-medium-ro_private_dataset
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.9763
- Wer Ortho: 104.4025
- Wer: 102.3457
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0288 | 20.0 | 100 | 3.3078 | 118.7421 | 116.9136 |
| 0.0015 | 40.0 | 200 | 3.6434 | 98.9937 | 97.6543 |
| 0.0017 | 60.0 | 300 | 3.6502 | 100.2516 | 99.1358 |
| 0.0002 | 80.0 | 400 | 3.8591 | 105.6604 | 103.5802 |
| 0.0001 | 100.0 | 500 | 3.9031 | 113.8365 | 111.9753 |
| 0.0001 | 120.0 | 600 | 3.9312 | 114.0881 | 112.0988 |
| 0.0001 | 140.0 | 700 | 3.9508 | 101.6352 | 99.7531 |
| 0.0001 | 160.0 | 800 | 3.9650 | 103.5220 | 101.7284 |
| 0.0001 | 180.0 | 900 | 3.9731 | 104.0252 | 101.9753 |
| 0.0001 | 200.0 | 1000 | 3.9763 | 104.4025 | 102.3457 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3