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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
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