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Whisper Base Ukrainian

This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_16_0 uk dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4984
  • Wer: 35.9409

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-06
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.5338 3.01 1000 0.5985 42.0862
0.4086 6.02 2000 0.5545 39.8889
0.336 9.02 3000 0.5347 38.2399
0.3672 13.0 4000 0.5165 37.2395
0.3862 16.01 5000 0.5096 36.7576
0.3298 19.02 6000 0.5040 36.5556
0.297 22.03 7000 0.5040 36.3153
0.3006 26.0 8000 0.4985 36.0172
0.3429 29.01 9000 0.4984 35.9409
0.2978 32.02 10000 0.4978 35.9423

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.2.dev0
  • Tokenizers 0.15.0
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Dataset used to train arun100/whisper-base-uk-1

Evaluation results