whisper-small-sr / README.md
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metadata
language:
  - sr
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: Whisper Small Serbian
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 13
          type: mozilla-foundation/common_voice_13_0
          config: sr
          split: test
          args: sr
        metrics:
          - name: Wer
            type: wer
            value: 17.41963509991312

Whisper Small Serbian

This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4671
  • Wer Ortho: 27.4565
  • Wer: 17.4196

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 2500

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.1403 1.44 250 0.2809 28.8913 19.2224
0.0664 2.87 500 0.2858 27.3696 17.9626
0.0315 4.31 750 0.3152 27.9348 17.4631
0.0174 5.75 1000 0.3578 28.1522 17.9844
0.0067 7.18 1250 0.4018 27.9130 17.9626
0.0015 8.62 1500 0.4535 28.6739 17.5717
0.0008 10.06 1750 0.4558 27.2174 17.1807
0.0005 11.49 2000 0.4585 27.4348 17.4848
0.0005 12.93 2250 0.4651 27.3478 17.3979
0.0005 14.37 2500 0.4671 27.4565 17.4196

Framework versions

  • Transformers 4.33.3
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3