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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-base |
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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 Base 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: 80.47772163527792 |
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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 Base Arabic |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) 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: 0.5856 |
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- Wer: 80.4777 |
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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: 5e-07 |
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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: 500 |
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- training_steps: 10000 |
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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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| 0.7392 | 1.53 | 500 | 0.8623 | 100.8133 | |
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| 0.5938 | 3.07 | 1000 | 0.7397 | 93.6651 | |
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| 0.5388 | 4.6 | 1500 | 0.6953 | 92.3005 | |
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| 0.4982 | 6.13 | 2000 | 0.6682 | 88.9392 | |
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| 0.4795 | 7.67 | 2500 | 0.6512 | 90.1524 | |
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| 0.4483 | 9.2 | 3000 | 0.6373 | 87.1234 | |
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| 0.4374 | 10.74 | 3500 | 0.6261 | 85.3144 | |
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| 0.4331 | 12.27 | 4000 | 0.6179 | 86.4290 | |
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| 0.4125 | 13.8 | 4500 | 0.6106 | 83.2865 | |
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| 0.3984 | 15.34 | 5000 | 0.6059 | 83.0676 | |
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| 0.4035 | 16.87 | 5500 | 0.6008 | 82.2165 | |
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| 0.3997 | 18.4 | 6000 | 0.5970 | 81.1195 | |
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| 0.3878 | 19.94 | 6500 | 0.5941 | 81.7153 | |
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| 0.3827 | 21.47 | 7000 | 0.5906 | 81.2559 | |
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| 0.3785 | 23.01 | 7500 | 0.5892 | 81.0506 | |
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| 0.372 | 24.54 | 8000 | 0.5882 | 81.4248 | |
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| 0.3655 | 26.07 | 8500 | 0.5865 | 81.0479 | |
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| 0.3697 | 27.61 | 9000 | 0.5856 | 80.4777 | |
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| 0.3658 | 29.14 | 9500 | 0.5849 | 80.6128 | |
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| 0.3539 | 30.67 | 10000 | 0.5848 | 80.6696 | |
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### Framework versions |
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- Transformers 4.37.0.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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