readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2_common_voice_accents_indian_only_rerun
    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_common_voice_accents_indian_only_rerun
  
  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: 1.2807
  
  ## 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: 48
  - eval_batch_size: 4
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 8
  - total_train_batch_size: 384
  - total_eval_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: 588
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 4.6205        | 25.0  | 400  | 1.4584          |
  | 0.3427        | 50.0  | 800  | 1.8377          |
  | 0.1213        | 75.0  | 1200 | 1.6086          |
  | 0.0643        | 100.0 | 1600 | 1.5136          |
  | 0.0433        | 125.0 | 2000 | 1.4882          |
  | 0.0323        | 150.0 | 2400 | 1.2204          |
  | 0.0265        | 175.0 | 2800 | 1.3034          |
  | 0.0206        | 200.0 | 3200 | 1.2866          |
  | 0.0191        | 225.0 | 3600 | 1.2337          |
  | 0.0148        | 250.0 | 4000 | 1.1729          |
  | 0.0121        | 275.0 | 4400 | 1.2059          |
  | 0.0105        | 300.0 | 4800 | 1.1246          |
  | 0.01          | 325.0 | 5200 | 1.1397          |
  | 0.0098        | 350.0 | 5600 | 1.1684          |
  | 0.0073        | 375.0 | 6000 | 1.1030          |
  | 0.0061        | 400.0 | 6400 | 1.2077          |
  | 0.0049        | 425.0 | 6800 | 1.2653          |
  | 0.0044        | 450.0 | 7200 | 1.1587          |
  | 0.0037        | 475.0 | 7600 | 1.2283          |
  | 0.0033        | 500.0 | 8000 | 1.1897          |
  | 0.0026        | 525.0 | 8400 | 1.2633          |
  | 0.0023        | 550.0 | 8800 | 1.2571          |
  | 0.002         | 575.0 | 9200 | 1.2807          |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  