readme: ---
  language:
  - hi
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - robust-speech-event
  - generated_from_trainer
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: ''
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7.0
        type: mozilla-foundation/common_voice_7_0
        args: hi
      metrics:
      - name: Test WER
        type: wer
        value: 38.18
  ---
  
  <!-- 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_7_0 - HI dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7346
  - Wer: 1.0479
  
  ## 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: 500
  - training_steps: 8000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.36  | 400  | 1.4595          | 1.0039 |
  | 4.7778        | 2.71  | 800  | 0.8082          | 1.0115 |
  | 0.6408        | 4.07  | 1200 | 0.7032          | 1.0079 |
  | 0.3937        | 5.42  | 1600 | 0.6889          | 1.0433 |
  | 0.3           | 6.78  | 2000 | 0.6820          | 1.0069 |
  | 0.3           | 8.14  | 2400 | 0.6670          | 1.0196 |
  | 0.226         | 9.49  | 2800 | 0.7216          | 1.0422 |
  | 0.197         | 10.85 | 3200 | 0.7669          | 1.0534 |
  | 0.165         | 12.2  | 3600 | 0.7517          | 1.0200 |
  | 0.1486        | 13.56 | 4000 | 0.7125          | 1.0357 |
  | 0.1486        | 14.92 | 4400 | 0.7447          | 1.0347 |
  | 0.122         | 16.27 | 4800 | 0.6899          | 1.0440 |
  | 0.1069        | 17.63 | 5200 | 0.7212          | 1.0350 |
  | 0.0961        | 18.98 | 5600 | 0.7417          | 1.0408 |
  | 0.086         | 20.34 | 6000 | 0.7402          | 1.0356 |
  | 0.086         | 21.69 | 6400 | 0.7761          | 1.0420 |
  | 0.0756        | 23.05 | 6800 | 0.7346          | 1.0369 |
  | 0.0666        | 24.41 | 7200 | 0.7506          | 1.0449 |
  | 0.0595        | 25.76 | 7600 | 0.7319          | 1.0476 |
  | 0.054         | 27.12 | 8000 | 0.7346          | 1.0479 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  