readme: ---
  license: apache-2.0
  language:
  - hi
  tags:
  - generated_from_trainer
  - hf-asr-leaderboard
  - robust-speech-event
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-300m-hi
    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-large-xls-r-300m-hi
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.4749
  - Wer: 0.9420
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - 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: 500
  - num_epochs: 50
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 9.8626        | 4.76  | 400  | 3.6151          | 1.0    |
  | 3.5463        | 9.52  | 800  | 3.5778          | 1.0    |
  | 3.4415        | 14.28 | 1200 | 3.4525          | 1.0    |
  | 3.0927        | 19.05 | 1600 | 2.6220          | 0.9860 |
  | 2.0573        | 23.8  | 2000 | 2.3974          | 0.9610 |
  | 1.5905        | 28.57 | 2400 | 2.4427          | 0.9558 |
  | 1.426         | 33.33 | 2800 | 2.4736          | 0.9475 |
  | 1.3147        | 38.09 | 3200 | 2.4494          | 0.9417 |
  | 1.2642        | 42.85 | 3600 | 2.4665          | 0.9450 |
  | 1.2289        | 47.62 | 4000 | 2.4749          | 0.9420 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.10.3
  