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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_Mixed
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_Mixed
          type: Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed
          args: 'config: ar, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 53.55042318175298

Whisper Tunisien

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

  • Loss: 0.9262
  • Wer: 53.5504

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: 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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.0933 4.5045 500 1.1956 61.0242
0.7416 9.0090 1000 0.9971 56.0895
0.5403 13.5135 1500 0.9140 53.4644
0.4315 18.0180 2000 0.8778 53.3783
0.2836 22.5225 2500 0.8948 53.0627
0.2513 27.0270 3000 0.9099 53.5074
0.2196 31.5315 3500 0.9215 53.6365
0.2199 36.0360 4000 0.9262 53.5504

Framework versions

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