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
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Dataset used to train Tomas1234/common_voice

Space using Tomas1234/common_voice 1

Evaluation results