readme: ---
  language:
  - hi
  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 - HI dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8111
  - Wer: 0.5177
  
  ## 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: 50.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 4.9733        | 2.59  | 500  | 5.0697          | 1.0    |
  | 3.3839        | 5.18  | 1000 | 3.3518          | 1.0    |
  | 2.0596        | 7.77  | 1500 | 1.3992          | 0.7869 |
  | 1.6102        | 10.36 | 2000 | 1.0712          | 0.6754 |
  | 1.4587        | 12.95 | 2500 | 0.9280          | 0.6361 |
  | 1.3667        | 15.54 | 3000 | 0.9281          | 0.6155 |
  | 1.3042        | 18.13 | 3500 | 0.9037          | 0.5921 |
  | 1.2544        | 20.73 | 4000 | 0.8996          | 0.5824 |
  | 1.2274        | 23.32 | 4500 | 0.8934          | 0.5797 |
  | 1.1763        | 25.91 | 5000 | 0.8643          | 0.5760 |
  | 1.149         | 28.5  | 5500 | 0.8251          | 0.5544 |
  | 1.1207        | 31.09 | 6000 | 0.8506          | 0.5527 |
  | 1.091         | 33.68 | 6500 | 0.8370          | 0.5366 |
  | 1.0613        | 36.27 | 7000 | 0.8345          | 0.5352 |
  | 1.0495        | 38.86 | 7500 | 0.8380          | 0.5321 |
  | 1.0345        | 41.45 | 8000 | 0.8285          | 0.5269 |
  | 1.0297        | 44.04 | 8500 | 0.7836          | 0.5141 |
  | 1.027         | 46.63 | 9000 | 0.8120          | 0.5180 |
  | 0.9876        | 49.22 | 9500 | 0.8109          | 0.5188 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu113
  - Datasets 1.18.1.dev0
  - Tokenizers 0.11.0
  