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whisper-small-et
This model is a fine-tuned version of openai/whisper-small on the following datasets: Common Voice 11, VoxPopuli and FLEURS.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
Estonian data from Common Voice 11, VoxPopuli and FLEURS corpora as both training and validation sets. Tested on Common Voice 11 test set.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 64
- eval_batch_size: 32
- 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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.1285 | 1.03 | 200 | 1.0640 | 53.4934 |
| 0.5163 | 2.05 | 400 | 0.6450 | 41.2428 |
| 0.2005 | 4.01 | 600 | 0.5600 | 36.6797 |
| 0.1188 | 5.03 | 800 | 0.5718 | 35.2847 |
| 0.0487 | 6.06 | 1000 | 0.5999 | 34.7500 |
| 0.0216 | 8.01 | 1200 | 0.6479 | 38.1906 |
| 0.016 | 9.04 | 1400 | 0.6655 | 39.5034 |
| 0.0085 | 10.06 | 1600 | 0.7027 | 33.9038 |
| 0.0079 | 12.02 | 1800 | 0.7207 | 39.5723 |
| 0.009 | 13.04 | 2000 | 0.7261 | 34.5973 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+rocm5.1.1
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
