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: 1.1508
  - Wer: 0.4908
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1500
  - num_epochs: 100.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.5841        | 9.26  | 500  | 3.2514          | 0.9941 |
  | 0.3992        | 18.52 | 1000 | 0.8790          | 0.6107 |
  | 0.2409        | 27.78 | 1500 | 1.0012          | 0.6366 |
  | 0.1447        | 37.04 | 2000 | 1.0167          | 0.6276 |
  | 0.1109        | 46.3  | 2500 | 1.0638          | 0.5653 |
  | 0.0797        | 55.56 | 3000 | 1.1447          | 0.5715 |
  | 0.0636        | 64.81 | 3500 | 1.1503          | 0.5316 |
  | 0.0466        | 74.07 | 4000 | 1.2227          | 0.5386 |
  | 0.0372        | 83.33 | 4500 | 1.1214          | 0.5225 |
  | 0.0239        | 92.59 | 5000 | 1.1375          | 0.4998 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  