readme: ---
  language:
  - hi
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_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_7_0 - HI dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4484
  - Wer: 1.0145
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 5.1844        | 3.4   | 500  | 5.2015          | 0.9999 |
  | 3.3962        | 6.8   | 1000 | 3.4017          | 1.0002 |
  | 2.5433        | 10.2  | 1500 | 1.6884          | 1.0222 |
  | 1.5099        | 13.6  | 2000 | 0.7929          | 1.0188 |
  | 1.2685        | 17.01 | 2500 | 0.6122          | 1.0191 |
  | 1.1844        | 20.41 | 3000 | 0.5434          | 1.0197 |
  | 1.0945        | 23.81 | 3500 | 0.5208          | 1.0316 |
  | 1.0506        | 27.21 | 4000 | 0.4941          | 1.0139 |
  | 1.0199        | 30.61 | 4500 | 0.4736          | 1.0106 |
  | 0.9546        | 34.01 | 5000 | 0.4664          | 1.0164 |
  | 0.9388        | 37.41 | 5500 | 0.4565          | 1.0085 |
  | 0.9125        | 40.81 | 6000 | 0.4636          | 1.0148 |
  | 0.8733        | 44.22 | 6500 | 0.4530          | 1.0154 |
  | 0.8829        | 47.62 | 7000 | 0.4494          | 1.0152 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.11.0
  