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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec_arabic_mdd_v2 |
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results: [] |
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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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# wav2vec_arabic_mdd_v2 |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2736 |
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- Wer: 0.0492 |
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- Cer: 0.0378 |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 20 |
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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 | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:|:------:| |
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| 5.2969 | 0.9951 | 102 | 4.4152 | 1.0 | 1.0 | |
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| 3.2462 | 2.0 | 205 | 3.2917 | 1.0 | 1.0 | |
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| 3.1998 | 2.9951 | 307 | 3.2287 | 1.0 | 1.0 | |
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| 3.2577 | 4.0 | 410 | 3.1610 | 1.0 | 1.0 | |
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| 2.4548 | 4.9951 | 512 | 2.5563 | 0.9881 | 0.9914 | |
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| 0.678 | 6.0 | 615 | 0.7636 | 0.2986 | 0.2701 | |
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| 0.1777 | 6.9951 | 717 | 0.3790 | 0.0925 | 0.0781 | |
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| 0.1097 | 8.0 | 820 | 0.3732 | 0.0865 | 0.0694 | |
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| 0.0737 | 8.9951 | 922 | 0.3027 | 0.0641 | 0.0511 | |
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| 0.0526 | 10.0 | 1025 | 0.2834 | 0.0699 | 0.0578 | |
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| 0.0471 | 10.9951 | 1127 | 0.2601 | 0.0541 | 0.0435 | |
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| 0.0349 | 12.0 | 1230 | 0.2803 | 0.0518 | 0.0396 | |
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| 0.029 | 12.9951 | 1332 | 0.2710 | 0.0502 | 0.0378 | |
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| 0.0225 | 14.0 | 1435 | 0.2835 | 0.0494 | 0.0378 | |
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| 0.023 | 14.9951 | 1537 | 0.2909 | 0.0483 | 0.0368 | |
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| 0.0247 | 16.0 | 1640 | 0.2725 | 0.0480 | 0.0361 | |
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| 0.035 | 16.9951 | 1742 | 0.2696 | 0.0489 | 0.0372 | |
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| 0.0156 | 18.0 | 1845 | 0.2742 | 0.0482 | 0.0364 | |
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| 0.0183 | 18.9951 | 1947 | 0.2741 | 0.0492 | 0.0376 | |
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| 0.0179 | 19.9024 | 2040 | 0.2736 | 0.0492 | 0.0378 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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