readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-xls-r-300m-ar-6
    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-6
  
  This model is a fine-tuned version of [MeshalAlamr/wav2vec2-xls-r-300m-ar-6](https://huggingface.co/MeshalAlamr/wav2vec2-xls-r-300m-ar-6) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 78.2951
  - Wer: 0.2040
  
  ## 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: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.0   | 85   | 75.3576         | 0.2131 |
  | No log        | 2.0   | 170  | 75.3215         | 0.2150 |
  | No log        | 3.0   | 255  | 75.5332         | 0.2201 |
  | No log        | 4.0   | 340  | 81.2835         | 0.2315 |
  | 94.75         | 5.0   | 425  | 78.3768         | 0.2422 |
  | 94.75         | 6.0   | 510  | 82.9389         | 0.2520 |
  | 94.75         | 7.0   | 595  | 76.7272         | 0.2496 |
  | 94.75         | 8.0   | 680  | 79.9325         | 0.2506 |
  | 94.75         | 9.0   | 765  | 82.2568         | 0.2507 |
  | 124.0193      | 10.0  | 850  | 78.7011         | 0.2415 |
  | 124.0193      | 11.0  | 935  | 81.2829         | 0.2396 |
  | 124.0193      | 12.0  | 1020 | 77.2370         | 0.2357 |
  | 124.0193      | 13.0  | 1105 | 77.4057         | 0.2347 |
  | 124.0193      | 14.0  | 1190 | 74.4764         | 0.2271 |
  | 112.7824      | 15.0  | 1275 | 78.7320         | 0.2355 |
  | 112.7824      | 16.0  | 1360 | 79.0120         | 0.2294 |
  | 112.7824      | 17.0  | 1445 | 82.3663         | 0.2240 |
  | 112.7824      | 18.0  | 1530 | 79.2765         | 0.2236 |
  | 98.8702       | 19.0  | 1615 | 78.1527         | 0.2242 |
  | 98.8702       | 20.0  | 1700 | 75.7842         | 0.2198 |
  | 98.8702       | 21.0  | 1785 | 78.2980         | 0.2217 |
  | 98.8702       | 22.0  | 1870 | 79.3180         | 0.2168 |
  | 98.8702       | 23.0  | 1955 | 77.7381         | 0.2155 |
  | 84.537        | 24.0  | 2040 | 78.1512         | 0.2131 |
  | 84.537        | 25.0  | 2125 | 80.4068         | 0.2116 |
  | 84.537        | 26.0  | 2210 | 75.5718         | 0.2075 |
  | 84.537        | 27.0  | 2295 | 78.4438         | 0.2078 |
  | 84.537        | 28.0  | 2380 | 79.6891         | 0.2086 |
  | 74.4149       | 29.0  | 2465 | 77.9115         | 0.2069 |
  | 74.4149       | 30.0  | 2550 | 78.2951         | 0.2040 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  