readme: ---
  language:
  - mr
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - mozilla-foundation/common_voice_8_0
  - mr
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: ''
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: Common Voice Corpus 8.0
        type: mozilla-foundation/common_voice_8_0
        args: mr
      metrics:
      - name: Test WER
        type: wer
        value: 38.27
      - name: Test CER
        type: cer
        value: 8.91
  ---
  
  <!-- 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 - MR dataset.
  It achieves the following results on the mozilla-foundation/common_voice_8_0 mr test set:
  
  - Without LM
    + WER: 48.53
    + CER: 10.63
     
  - With LM
    + WER: 38.27
    + CER: 8.91
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 2000
  - num_epochs: 400.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer    |
  |:-------------:|:------:|:----:|:---------------:|:------:|
  | 4.2706        | 22.73  | 500  | 4.0174          | 1.0    |
  | 3.2492        | 45.45  | 1000 | 3.2309          | 0.9908 |
  | 1.9709        | 68.18  | 1500 | 1.0651          | 0.8440 |
  | 1.4088        | 90.91  | 2000 | 0.5765          | 0.6550 |
  | 1.1326        | 113.64 | 2500 | 0.4842          | 0.5760 |
  | 0.9709        | 136.36 | 3000 | 0.4785          | 0.6013 |
  | 0.8433        | 159.09 | 3500 | 0.5048          | 0.5419 |
  | 0.7404        | 181.82 | 4000 | 0.5052          | 0.5339 |
  | 0.6589        | 204.55 | 4500 | 0.5237          | 0.5897 |
  | 0.5831        | 227.27 | 5000 | 0.5166          | 0.5447 |
  | 0.5375        | 250.0  | 5500 | 0.5292          | 0.5487 |
  | 0.4784        | 272.73 | 6000 | 0.5480          | 0.5596 |
  | 0.4421        | 295.45 | 6500 | 0.5682          | 0.5467 |
  | 0.4047        | 318.18 | 7000 | 0.5681          | 0.5447 |
  | 0.3779        | 340.91 | 7500 | 0.5783          | 0.5347 |
  | 0.3525        | 363.64 | 8000 | 0.5856          | 0.5367 |
  | 0.3393        | 386.36 | 8500 | 0.5960          | 0.5359 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu113
  - Datasets 1.18.1.dev0
  - Tokenizers 0.11.0
  