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Whisper Small lt - Lithuanian
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3840
- Wer: 32.4971
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: 250
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3788 | 0.9 | 500 | 0.4432 | 45.1716 |
| 0.2087 | 1.8 | 1000 | 0.3671 | 37.6456 |
| 0.0961 | 2.7 | 1500 | 0.3548 | 35.5703 |
| 0.0479 | 3.6 | 2000 | 0.3609 | 34.1709 |
| 0.0157 | 4.5 | 2500 | 0.3665 | 33.3400 |
| 0.0089 | 5.4 | 3000 | 0.3775 | 32.7754 |
| 0.0038 | 6.29 | 3500 | 0.3826 | 32.5607 |
| 0.0033 | 7.19 | 4000 | 0.3840 | 32.4971 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
