readme: ---
  language:
  - ar
  license: apache-2.0
  tags:
  - ar
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
  - hf-asr-leaderboard
  - robust-speech-event
  datasets:
  - common_voice
  model-index:
  - name: XLS-R-300M - Arabic
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: ar
      metrics:
      - name: Test WER
        type: wer
        value: 1.0
      - name: Test CER
        type: cer
        value: 1.0
  ---
  
  <!-- 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
  
  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 - AR dataset.
  It achieves the following results on the evaluation set:
  - eval_loss: 3.0191
  - eval_wer: 1.0
  - eval_runtime: 252.2389
  - eval_samples_per_second: 30.217
  - eval_steps_per_second: 0.476
  - epoch: 1.0
  - step: 340
  
  ## 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: 0.0005
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 2000
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  
  #### Evaluation Commands
  
  Please use the evaluation script `eval.py` included in the repo.
  
  1. To evaluate on `speech-recognition-community-v2/dev_data`
  
  ```bash
  python eval.py --model_id nouamanetazi/wav2vec2-xls-r-300m-ar --dataset speech-recognition-community-v2/dev_data --config ar --split validation --chunk_length_s 5.0 --stride_length_s 1.0
  ```