readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-xls-r-300m-ar-8
    results: []
  ---
  
  <!-- 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-xls-r-300m-ar-8
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 76.6942
  - Wer: 0.2108
  
  ## 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: 64
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 256
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 60
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 6295.0487     | 4.71  | 400  | 615.8572        | 1.0    |
  | 1464.0058     | 9.41  | 800  | 111.7187        | 0.5361 |
  | 425.6333      | 14.12 | 1200 | 80.7770         | 0.3446 |
  | 280.069       | 18.82 | 1600 | 74.0422         | 0.2980 |
  | 213.0118      | 23.53 | 2000 | 78.4876         | 0.2783 |
  | 175.6819      | 28.24 | 2400 | 70.4845         | 0.2491 |
  | 148.5846      | 32.94 | 2800 | 70.5758         | 0.2443 |
  | 131.1029      | 37.65 | 3200 | 75.3770         | 0.2371 |
  | 116.7131      | 42.35 | 3600 | 78.7061         | 0.2268 |
  | 105.369       | 47.06 | 4000 | 76.4783         | 0.2210 |
  | 97.0829       | 51.76 | 4400 | 76.6051         | 0.2153 |
  | 90.4009       | 56.47 | 4800 | 76.6942         | 0.2108 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  