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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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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Arabic |
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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: mozilla-foundation/common_voice_16_0 ar |
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type: mozilla-foundation/common_voice_16_0 |
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config: ar |
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split: test |
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args: ar |
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metrics: |
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- name: Wer |
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type: wer |
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value: 58.90729282066525 |
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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 Small Arabic |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_16_0 ar dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4005 |
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- Wer: 58.9073 |
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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-06 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 50 |
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- training_steps: 5000 |
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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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| 0.3404 | 1.53 | 500 | 0.4606 | 66.6216 | |
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| 0.2707 | 3.07 | 1000 | 0.4295 | 66.8500 | |
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| 0.2427 | 4.6 | 1500 | 0.4124 | 61.1662 | |
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| 0.2131 | 6.13 | 2000 | 0.4056 | 62.3038 | |
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| 0.2085 | 7.67 | 2500 | 0.4012 | 62.2754 | |
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| 0.1904 | 9.2 | 3000 | 0.3976 | 59.7341 | |
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| 0.1836 | 10.74 | 3500 | 0.4005 | 58.9073 | |
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| 0.1653 | 12.27 | 4000 | 0.3989 | 59.7774 | |
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| 0.1693 | 13.8 | 4500 | 0.3983 | 59.9462 | |
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| 0.1616 | 15.34 | 5000 | 0.3984 | 59.8300 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.2.dev0 |
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- Tokenizers 0.15.0 |
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