Whisper Large_v2 RO CV17
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.6152
- Wer: 47.5102
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: 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 |
|---|---|---|---|---|
| 0.5004 | 5.4945 | 1000 | 1.1554 | 106.2565 |
| 0.0896 | 10.9890 | 2000 | 1.3810 | 51.0737 |
| 0.0121 | 16.4835 | 3000 | 1.5371 | 49.9013 |
| 0.0027 | 21.9780 | 4000 | 1.5901 | 49.1468 |
| 0.0008 | 27.4725 | 5000 | 1.6152 | 47.5102 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.19.1
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Model tree for AdaCodruta/whisper_ro_MilDB
Base model
openai/whisper-large-v3 Finetuned
openai/whisper-large-v3-turboDataset used to train AdaCodruta/whisper_ro_MilDB
Evaluation results
- Wer on Common Voice 17.0self-reported47.510