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metadata
library_name: transformers
language:
  - ru
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - custom
metrics:
  - wer
model-index:
  - name: Whisper Small RU (Phone) v6 - Stepler
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: ru_audiobooks_sova
          type: custom
          args: 'config: ru, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 14.931947459319

Whisper Small RU (Phone) v6 - Stepler

This model is a fine-tuned version of openai/whisper-small on the ru_audiobooks_sova dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1732
  • Wer: 14.9319

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: 1000
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2325 0.3501 4000 0.2328 20.7527
0.1867 0.7002 8000 0.2006 18.3470
0.0968 1.0503 12000 0.1889 16.9944
0.1109 1.4004 16000 0.1805 16.6653
0.0947 1.7505 20000 0.1746 15.7622
0.0435 2.1007 24000 0.1756 15.4416
0.0566 2.4508 28000 0.1756 15.1253
0.0462 2.8009 32000 0.1732 14.9319

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu124
  • Datasets 2.21.0
  • Tokenizers 0.19.1