111 lines
3.5 KiB
Markdown
111 lines
3.5 KiB
Markdown
---
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library_name: transformers
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language:
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- ar
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license: mit
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base_model: openai/whisper-large-v3-turbo
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tags:
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- generated_from_trainer
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datasets:
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- fixie-ai/common_voice_17_0
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- google/fleurs
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- UBC-NLP/Casablanca
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- deepdml/Tunisian_MSA
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- ymoslem/MediaSpeech
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metrics:
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- wer
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model-index:
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- name: Whisper Turbo ar
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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: Common Voice 17.0
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type: fixie-ai/common_voice_17_0
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metrics:
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- name: Wer
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type: wer
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value: 18.89976313325132
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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 Turbo ar
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This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Common Voice 17.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1973
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- Wer: 18.8998
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- Cer: 5.0561
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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: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.04
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- training_steps: 18000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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|:-------------:|:------:|:-----:|:---------------:|:-------:|:------:|
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| 0.5358 | 0.0556 | 1000 | 0.3047 | 26.8192 | 8.1187 |
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| 0.3875 | 0.1111 | 2000 | 0.2829 | 27.2654 | 7.5340 |
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| 0.2546 | 0.1667 | 3000 | 0.2629 | 24.2008 | 6.7543 |
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| 0.1702 | 0.2222 | 4000 | 0.2628 | 23.4884 | 6.5769 |
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| 0.1075 | 0.2778 | 5000 | 0.2584 | 23.9566 | 6.6370 |
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| 0.0859 | 0.3333 | 6000 | 0.2569 | 24.5221 | 6.6761 |
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| 0.06 | 0.3889 | 7000 | 0.2479 | 22.1828 | 6.1018 |
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| 0.0539 | 0.4444 | 8000 | 0.2461 | 22.6143 | 6.2866 |
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| 0.0427 | 0.5 | 9000 | 0.2402 | 23.1083 | 6.3401 |
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| 0.0341 | 0.5556 | 10000 | 0.2356 | 22.2012 | 6.0513 |
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| 0.0275 | 0.6111 | 11000 | 0.2338 | 20.7378 | 5.6669 |
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| 0.0204 | 0.6667 | 12000 | 0.2296 | 21.1381 | 5.7997 |
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| 0.0156 | 0.7222 | 13000 | 0.2324 | 21.9037 | 5.8359 |
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| 0.0162 | 0.7778 | 14000 | 0.2214 | 20.4825 | 5.5345 |
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| 0.0163 | 0.8333 | 15000 | 0.2131 | 21.0426 | 5.6430 |
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| 0.0127 | 0.8889 | 16000 | 0.2093 | 19.5791 | 5.2782 |
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| 0.006 | 0.9444 | 17000 | 0.2083 | 19.8197 | 5.2719 |
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| 0.0072 | 1.0 | 18000 | 0.1973 | 18.8998 | 5.0561 |
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### Framework versions
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- Transformers 4.48.0.dev0
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- Pytorch 2.5.1+cu121
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- Datasets 3.6.0
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- Tokenizers 0.21.0
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## Citation
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Please cite the model using the following BibTeX entry:
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```bibtex
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@misc{deepdml/whisper-large-v3-turbo-ar-mix-norm,
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title={Fine-tuned Whisper turbo ASR model for speech recognition in Arabic},
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author={Jimenez, David},
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howpublished={\url{https://huggingface.co/deepdml/whisper-large-v3-turbo-ar-mix-norm}},
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year={2026}
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}
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```
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