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whisper-large-v2-et-children
This model is a fine-tuned version of agnesluhtaru/whisper-large-et-ERR2020-v2 on an Estonian children's speech dataset.
More information about the model's performance and the data used for evaluation and training:
Luhtaru, Agnes; Jaaska, Rauno; Kruusamäe, Karl; Fishel, Mark (2023). Automatic Transcription for Estonian Children’s Speech. In: Proceedings of the 24th Nordic Conference on Computational Linguistics. https://openreview.net/forum?id=xbPTfBIUby
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0302 | 4.03 | 500 | 0.2971 | 16.2892 |
| 0.0042 | 8.06 | 1000 | 0.3406 | 15.8551 |
| 0.0017 | 12.1 | 1500 | 0.3714 | 15.5585 |
| 0.0009 | 16.13 | 2000 | 0.3934 | 15.6445 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+rocm5.1.1
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
