| --- |
| library_name: transformers |
| language: |
| - ar |
| license: apache-2.0 |
| base_model: openai/whisper-base |
| tags: |
| - generated_from_trainer |
| datasets: |
| - google/fleurs |
| - fixie-ai/common_voice_17_0 |
| - UBC-NLP/Casablanca |
| - ymoslem/MediaSpeech |
| - deepdml/Tunisian_MSA |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Base ar |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 17.0 |
| type: google/fleurs |
| metrics: |
| - name: Wer |
| type: wer |
| value: 40.550118433374344 |
| --- |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # Whisper Base ar |
|
|
| This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 17.0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5179 |
| - Wer: 40.5501 |
| - Cer: 13.2382 |
|
|
| ## 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: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.04 |
| - training_steps: 18000 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
| |:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:| |
| | 0.7397 | 0.0556 | 1000 | 0.6305 | 54.8668 | 18.9365 | |
| | 0.3962 | 0.1111 | 2000 | 0.5805 | 50.5793 | 16.9481 | |
| | 0.1913 | 0.1667 | 3000 | 0.5593 | 48.8019 | 16.2853 | |
| | 0.1031 | 0.2222 | 4000 | 0.5390 | 46.7766 | 15.6262 | |
| | 0.0743 | 0.2778 | 5000 | 0.5193 | 46.1321 | 15.5048 | |
| | 0.0463 | 0.3333 | 6000 | 0.5074 | 44.1857 | 14.5137 | |
| | 0.0296 | 1.0197 | 7000 | 0.5135 | 43.6074 | 14.0715 | |
| | 0.0288 | 1.0752 | 8000 | 0.5119 | 43.6514 | 14.6808 | |
| | 0.0232 | 1.1308 | 9000 | 0.4999 | 41.8538 | 13.6624 | |
| | 0.022 | 1.1863 | 10000 | 0.4930 | 41.8813 | 13.6632 | |
| | 0.0226 | 1.2419 | 11000 | 0.4779 | 41.8208 | 13.8859 | |
| | 0.0213 | 1.2974 | 12000 | 0.4795 | 41.0569 | 13.3648 | |
| | 0.0194 | 1.353 | 13000 | 0.4831 | 41.0881 | 13.3223 | |
| | 0.0148 | 2.0393 | 14000 | 0.5064 | 41.2644 | 13.4050 | |
| | 0.0131 | 2.0949 | 15000 | 0.5116 | 41.2570 | 13.5709 | |
| | 0.0116 | 2.1504 | 16000 | 0.5102 | 40.6860 | 13.2589 | |
| | 0.0088 | 2.206 | 17000 | 0.5196 | 40.4859 | 13.2482 | |
| | 0.0129 | 2.2616 | 18000 | 0.5179 | 40.5501 | 13.2382 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.48.0.dev0 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.0 |
| |
| ## Citation |
| |
| Please cite the model using the following BibTeX entry: |
| |
| ```bibtex |
| @misc{deepdml/whisper-base-ar-mix-norm, |
| title={Fine-tuned Whisper base ASR model for speech recognition in Arabic}, |
| author={Jimenez, David}, |
| howpublished={\url{https://huggingface.co/deepdml/whisper-base-ar-mix-norm}}, |
| year={2026} |
| } |
| ``` |
| |
