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--- |
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language: |
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- ar |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Tunisien |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Tunisian_dataset_STT-TTS15s_filtred1.0 |
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type: Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0 |
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args: 'config: ar, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 104.92910195813639 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper Tunisien |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Tunisian_dataset_STT-TTS15s_filtred1.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.9037 |
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- Wer: 104.9291 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-07 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 15000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:--------:|:-----:|:---------------:|:--------:| |
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| 1.2369 | 7.7519 | 1000 | 3.2094 | 117.6907 | |
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| 1.0283 | 15.5039 | 2000 | 3.0674 | 110.6685 | |
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| 0.9629 | 23.2558 | 3000 | 3.0180 | 130.3174 | |
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| 0.893 | 31.0078 | 4000 | 2.9887 | 126.7387 | |
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| 0.835 | 38.7597 | 5000 | 2.9676 | 103.5111 | |
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| 0.7907 | 46.5116 | 6000 | 2.9500 | 107.2248 | |
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| 0.7624 | 54.2636 | 7000 | 2.9370 | 107.5625 | |
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| 0.7624 | 62.0155 | 8000 | 2.9270 | 104.4564 | |
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| 0.7198 | 69.7674 | 9000 | 2.9200 | 104.3889 | |
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| 0.6818 | 77.5194 | 10000 | 2.9143 | 111.6138 | |
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| 0.7245 | 85.2713 | 11000 | 2.9099 | 104.5240 | |
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| 0.6762 | 93.0233 | 12000 | 2.9071 | 104.5915 | |
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| 0.6691 | 100.7752 | 13000 | 2.9052 | 104.8616 | |
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| 0.6366 | 108.5271 | 14000 | 2.9040 | 104.2539 | |
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| 0.6801 | 116.2791 | 15000 | 2.9037 | 104.9291 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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