readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-xlsr-korean-aihub-900
    results: []
  language:
  - ko
  ---
  
  <!-- 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-xlsr-korean-aihub-900
  
  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: 0.2659
  - Wer: 0.1089
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 700
  - num_epochs: 50
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | PER    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 7.0213        | 3.51  | 200  | 2.5580          | 0.9872 |
  | 2.4456        | 7.02  | 400  | 2.4060          | 0.9872 |
  | 2.2322        | 10.53 | 600  | 2.0604          | 0.9872 |
  | 1.9241        | 14.04 | 800  | 1.1675          | 0.5440 |
  | 0.8402        | 17.54 | 1000 | 0.4376          | 0.2035 |
  | 0.4796        | 21.05 | 1200 | 0.3261          | 0.1540 |
  | 0.339         | 24.56 | 1400 | 0.2918          | 0.1375 |
  | 0.2688        | 28.07 | 1600 | 0.2872          | 0.1310 |
  | 0.2338        | 31.58 | 1800 | 0.2732          | 0.1218 |
  | 0.212         | 35.09 | 2000 | 0.2654          | 0.1166 |
  | 0.1939        | 38.6  | 2200 | 0.2658          | 0.1087 |
  | 0.1738        | 42.11 | 2400 | 0.2692          | 0.1094 |
  | 0.1601        | 45.61 | 2600 | 0.2666          | 0.1107 |
  | 0.1587        | 49.12 | 2800 | 0.2659          | 0.1089 |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1