readme: ---
  tags:
  - generated_from_trainer
  - robust-speech-event 
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-300m-spanish-custom
    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-spanish-custom
  
  This model was trained from scratch on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - eval_loss: 0.2245
  - eval_wer: 0.2082
  - eval_runtime: 801.6784
  - eval_samples_per_second: 18.822
  - eval_steps_per_second: 2.354
  - epoch: 0.76
  - step: 8400
  
  ## 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: 0.0002
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 200
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.11.0
  