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TunLangModel_test1.12

Automatic Speech Recognition
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TunLangModel_test1.12 / README.md
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metadata
language:
  - ar
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0
metrics:
  - wer
model-index:
  - name: Whisper Tunisien
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Tunisian_dataset_STT-TTS15s_filtred1.0
          type: Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0
          args: 'config: ar, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 104.92910195813639

Whisper Tunisien

This model is a fine-tuned version of openai/whisper-small on the Tunisian_dataset_STT-TTS15s_filtred1.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 2.9037
  • Wer: 104.9291

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-07
  • train_batch_size: 8
  • 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
1.2369 7.7519 1000 3.2094 117.6907
1.0283 15.5039 2000 3.0674 110.6685
0.9629 23.2558 3000 3.0180 130.3174
0.893 31.0078 4000 2.9887 126.7387
0.835 38.7597 5000 2.9676 103.5111
0.7907 46.5116 6000 2.9500 107.2248
0.7624 54.2636 7000 2.9370 107.5625
0.7624 62.0155 8000 2.9270 104.4564
0.7198 69.7674 9000 2.9200 104.3889
0.6818 77.5194 10000 2.9143 111.6138
0.7245 85.2713 11000 2.9099 104.5240
0.6762 93.0233 12000 2.9071 104.5915
0.6691 100.7752 13000 2.9052 104.8616
0.6366 108.5271 14000 2.9040 104.2539
0.6801 116.2791 15000 2.9037 104.9291

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1