readme: ---
  language:
  - hi
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - Openslr Multilingual
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  model-index:
  - name: Wav2Vec2_xls_r_300m_hi_final
    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. -->
  
  # Wav2Vec2_xls_r_300m_hi_final
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the ['Openslr Multilingual and code-switching ASR challenge'](http://www.openslr.org/103/) dataset and ['mozilla-foundation/common_voice_7_0'](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0) dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3035
  - Wer: 0.3137
  - Cer: 0.0972
  
  ## 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: 0.0001
  - train_batch_size: 16
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 100
  - num_epochs: 8
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
  | 0.9821        | 0.64  | 400  | 0.5059          | 0.4783 | 0.1573 |
  | 0.6861        | 1.28  | 800  | 0.4201          | 0.4247 | 0.1356 |
  | 0.585         | 1.92  | 1200 | 0.3797          | 0.3811 | 0.1210 |
  | 0.5193        | 2.56  | 1600 | 0.3577          | 0.3652 | 0.1152 |
  | 0.4583        | 3.21  | 2000 | 0.3422          | 0.3519 | 0.1111 |
  | 0.4282        | 3.85  | 2400 | 0.3261          | 0.3450 | 0.1071 |
  | 0.3951        | 4.49  | 2800 | 0.3201          | 0.3325 | 0.1048 |
  | 0.3619        | 5.13  | 3200 | 0.3167          | 0.3296 | 0.1030 |
  | 0.345         | 5.77  | 3600 | 0.3157          | 0.3210 | 0.1013 |
  | 0.338         | 6.41  | 4000 | 0.3051          | 0.3143 | 0.0982 |
  | 0.3155        | 7.05  | 4400 | 0.3059          | 0.3154 | 0.0986 |
  | 0.3057        | 7.69  | 4800 | 0.3035          | 0.3137 | 0.0972 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  