readme: ---
  language:
  - ur
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_9_0
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_9_0
  metrics:
  - wer
  model-index:
  - name: XLS-R-300M - Urdu
    results:
    - task:
        type: automatic-speech-recognition
        name: Speech Recognition
      dataset:
        type: mozilla-foundation/common_voice_9_0
        name: Common Voice 9
        args: ur
      metrics:
      - type: wer
        value: 23.750
        name: Test WER
      - name: Test CER
        type: cer
        value: 8.310
  ---
  
  <!-- 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. -->
  
  # 
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - UR dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4147
  - Wer: 0.3172
  - Cer: 0.1050
  
  ## 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: 7.5e-05
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - training_steps: 5108
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
  | 3.2894        | 7.83  | 400  | 3.1501          | 1.0    | 1.0    |
  | 1.8586        | 15.68 | 800  | 0.8871          | 0.6721 | 0.2402 |
  | 1.3431        | 23.52 | 1200 | 0.5813          | 0.5502 | 0.1939 |
  | 1.2052        | 31.37 | 1600 | 0.4956          | 0.4788 | 0.1665 |
  | 1.1097        | 39.21 | 2000 | 0.4447          | 0.4143 | 0.1397 |
  | 1.0528        | 47.06 | 2400 | 0.4439          | 0.3961 | 0.1333 |
  | 0.9939        | 54.89 | 2800 | 0.4348          | 0.4014 | 0.1379 |
  | 0.9441        | 62.74 | 3200 | 0.4236          | 0.3653 | 0.1223 |
  | 0.913         | 70.58 | 3600 | 0.4309          | 0.3475 | 0.1157 |
  | 0.8678        | 78.43 | 4000 | 0.4270          | 0.3337 | 0.1110 |
  | 0.8414        | 86.27 | 4400 | 0.4158          | 0.3220 | 0.1070 |
  | 0.817         | 94.12 | 4800 | 0.4185          | 0.3231 | 0.1072 |
  
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.1.1.dev0
  - Tokenizers 0.12.1
  