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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_Mixed |
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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_Mixed |
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type: Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed |
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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: 44.46994692296657 |
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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_Mixed dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1841 |
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- Wer: 44.4699 |
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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-05 |
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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: 4000 |
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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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| 0.3626 | 4.5045 | 500 | 0.8379 | 53.0340 | |
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| 0.0527 | 9.0090 | 1000 | 0.9350 | 48.5440 | |
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| 0.0111 | 13.5135 | 1500 | 1.0400 | 49.4907 | |
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| 0.0049 | 18.0180 | 2000 | 1.1030 | 44.6564 | |
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| 0.0017 | 22.5225 | 2500 | 1.1338 | 44.7568 | |
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| 0.0014 | 27.0270 | 3000 | 1.1618 | 44.8142 | |
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| 0.0009 | 31.5315 | 3500 | 1.1784 | 44.8429 | |
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| 0.0009 | 36.0360 | 4000 | 1.1841 | 44.4699 | |
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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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