readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-large-xlsr-korean-demo-colab-2
    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-xlsr-korean-demo-colab-2
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2481
  - Wer: 0.2480
  
  ## 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: 4
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 8
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 4.7387        | 2.12  | 400  | 3.1791          | 1.0    |
  | 1.3766        | 4.23  | 800  | 0.4876          | 0.5264 |
  | 0.476         | 6.35  | 1200 | 0.2955          | 0.3648 |
  | 0.3209        | 8.46  | 1600 | 0.2926          | 0.3473 |
  | 0.2591        | 10.58 | 2000 | 0.2723          | 0.3094 |
  | 0.2055        | 12.7  | 2400 | 0.2746          | 0.3027 |
  | 0.1802        | 14.81 | 2800 | 0.2672          | 0.2976 |
  | 0.1552        | 16.93 | 3200 | 0.2822          | 0.2807 |
  | 0.1413        | 19.05 | 3600 | 0.2652          | 0.2856 |
  | 0.1232        | 21.16 | 4000 | 0.2631          | 0.2655 |
  | 0.1146        | 23.28 | 4400 | 0.2561          | 0.2574 |
  | 0.1086        | 25.4  | 4800 | 0.2461          | 0.2527 |
  | 0.0944        | 27.51 | 5200 | 0.2521          | 0.2535 |
  | 0.0881        | 29.63 | 5600 | 0.2481          | 0.2480 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  