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whisper-small-uz-with-uzbekvoice

Automatic Speech Recognition
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TensorBoard
Safetensors
Uzbek
whisper
hf-asr-leaderboard
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metadata
language:
  - uz
license: apache-2.0
base_model: openai/whisper-small
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_16_1
metrics:
  - wer
model-index:
  - name: Whisper Small Uz - Aslon Khamidov -- with Uzbek Voice dataset
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 16.1
          type: mozilla-foundation/common_voice_16_1
          config: uz
          split: test
          args: 'config: uz, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 30.20491240338149

Whisper Small Uz - Aslon Khamidov -- with Uzbek Voice dataset

This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3052
  • Wer: 30.2049

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: 500
  • training_steps: 15000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.4689 0.0210 1000 0.5616 48.2462
0.3234 0.0420 2000 0.4695 44.8210
0.3078 0.0630 3000 0.4184 38.8747
0.2845 0.0840 4000 0.3955 36.2861
0.2771 0.1050 5000 0.3720 35.5344
0.2459 0.1260 6000 0.3649 35.9415
0.2482 0.1470 7000 0.3499 34.3993
0.26 0.1680 8000 0.3389 32.9183
0.2128 0.1891 9000 0.3321 33.2493
0.2092 0.2101 10000 0.3215 31.4973
0.1942 0.2311 11000 0.3194 31.0465
0.1912 0.2521 12000 0.3184 31.2850
0.2199 0.2731 13000 0.3100 30.6395
0.1861 0.2941 14000 0.3059 30.8667
0.2344 0.3151 15000 0.3052 30.2049

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.2.0
  • Datasets 2.19.2
  • Tokenizers 0.19.1