readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: wav2vec2-large-xls-r-300m-sanitycheck
    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-sanitycheck
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0092
  - Accuracy: 1.0
  
  ## 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: 0.0001
  - 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
  - num_epochs: 12
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.14  | 8    | 0.8034          | 0.4737   |
  | No log        | 2.29  | 16   | 0.6803          | 0.5263   |
  | No log        | 3.43  | 24   | 0.4867          | 1.0      |
  | 0.5907        | 4.57  | 32   | 0.1781          | 0.9474   |
  | 0.5907        | 5.71  | 40   | 0.2168          | 0.9474   |
  | 0.5907        | 6.86  | 48   | 0.2403          | 0.9474   |
  | 0.5907        | 8.0   | 56   | 0.0143          | 1.0      |
  | 0.0932        | 9.14  | 64   | 0.0124          | 1.0      |
  | 0.0932        | 10.29 | 72   | 0.0089          | 1.0      |
  | 0.0932        | 11.43 | 80   | 0.0092          | 1.0      |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.17.0
  - Tokenizers 0.10.3
  