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--- |
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tags: |
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- generated_from_trainer |
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base_model: batoula187/wav2vec2-large-xls-r-300m-arabic-colab |
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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-arabic-colab |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: common_voice_17_0 |
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type: common_voice_17_0 |
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config: ar |
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split: test[:10%] |
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args: ar |
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metrics: |
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- type: wer |
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value: 0.627304825421734 |
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name: Wer |
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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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# wav2vec2-large-xls-r-300m-arabic-colab |
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This model is a fine-tuned version of [batoula187/wav2vec2-large-xls-r-300m-arabic-colab](https://huggingface.co/batoula187/wav2vec2-large-xls-r-300m-arabic-colab) 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: 1.5330 |
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- Wer: 0.6273 |
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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: 0.0003 |
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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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- gradient_accumulation_steps: 3 |
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- total_train_batch_size: 24 |
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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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- num_epochs: 30 |
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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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| 0.0457 | 1.6901 | 200 | 1.5030 | 0.6377 | |
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| 0.0408 | 3.3803 | 400 | 1.4683 | 0.6503 | |
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| 0.0693 | 5.0704 | 600 | 1.6023 | 0.6897 | |
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| 0.0766 | 6.7606 | 800 | 1.3947 | 0.6709 | |
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| 0.0653 | 8.4507 | 1000 | 1.5052 | 0.6858 | |
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| 0.0542 | 10.1408 | 1200 | 1.6550 | 0.6999 | |
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| 0.0535 | 11.8310 | 1400 | 1.4820 | 0.6591 | |
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| 0.0645 | 13.5211 | 1600 | 1.5134 | 0.6732 | |
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| 0.0583 | 15.2113 | 1800 | 1.4606 | 0.6561 | |
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| 0.0551 | 16.9014 | 2000 | 1.4476 | 0.6534 | |
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| 0.0462 | 18.5915 | 2200 | 1.5556 | 0.6557 | |
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| 0.0447 | 20.2817 | 2400 | 1.5289 | 0.6503 | |
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| 0.0395 | 21.9718 | 2600 | 1.5145 | 0.6434 | |
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| 0.0327 | 23.6620 | 2800 | 1.5916 | 0.6475 | |
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| 0.0317 | 25.3521 | 3000 | 1.5830 | 0.6526 | |
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| 0.0276 | 27.0423 | 3200 | 1.5935 | 0.6432 | |
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| 0.026 | 28.7324 | 3400 | 1.5330 | 0.6273 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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