readme: ---
  language:
  - pa-IN
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: ''
    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. -->
  
  # 
  
  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_8_0 - PA-IN dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6864
  - Wer: 0.6707
  
  ## 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: 32
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 200.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer    |
  |:-------------:|:------:|:----:|:---------------:|:------:|
  | 4.3322        | 14.81  | 400  | 3.7450          | 1.0    |
  | 3.2662        | 29.63  | 800  | 3.2571          | 0.9996 |
  | 1.6408        | 44.44  | 1200 | 0.9098          | 0.8162 |
  | 1.2289        | 59.26  | 1600 | 0.6757          | 0.7099 |
  | 1.0551        | 74.07  | 2000 | 0.6417          | 0.7044 |
  | 0.966         | 88.89  | 2400 | 0.6365          | 0.6789 |
  | 0.8713        | 103.7  | 2800 | 0.6617          | 0.6954 |
  | 0.8055        | 118.52 | 3200 | 0.6371          | 0.6762 |
  | 0.7489        | 133.33 | 3600 | 0.6798          | 0.6911 |
  | 0.7073        | 148.15 | 4000 | 0.6567          | 0.6731 |
  | 0.6609        | 162.96 | 4400 | 0.6742          | 0.6840 |
  | 0.6435        | 177.78 | 4800 | 0.6862          | 0.6633 |
  | 0.6282        | 192.59 | 5200 | 0.6865          | 0.6731 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.4.dev0
  - Tokenizers 0.11.0
  