readme: ---
  
  model-index:
  - name: wav2vec2-large-xlsr-arabic-common_voice-10_epochs
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # wav2vec2-large-xlsr-arabic-common_voice-10_epochs
  
  This model was trained from scratch on an unkown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3581
  - Wer: 0.4555
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 0.0003
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.1701        | 0.9   | 400  | 3.1599          | 1.0    |
  | 0.8933        | 1.8   | 800  | 0.7198          | 0.7877 |
  | 0.5849        | 2.7   | 1200 | 0.5046          | 0.6253 |
  | 0.3858        | 3.6   | 1600 | 0.4247          | 0.5561 |
  | 0.3083        | 4.49  | 2000 | 0.4026          | 0.5251 |
  | 0.2556        | 5.39  | 2400 | 0.4010          | 0.5051 |
  | 0.2221        | 6.29  | 2800 | 0.3765          | 0.4861 |
  | 0.2026        | 7.19  | 3200 | 0.3652          | 0.4794 |
  | 0.1996        | 8.09  | 3600 | 0.3627          | 0.4660 |
  | 0.1755        | 8.99  | 4000 | 0.3582          | 0.4619 |
  | 0.1697        | 9.89  | 4400 | 0.3581          | 0.4555 |
  
  
  ### Framework versions
  
  - Transformers 4.6.0
  - Pytorch 1.8.1+cu102
  - Datasets 1.6.2
  - Tokenizers 0.10.2
  