readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: korean-aihub-learning-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. -->
  
  # korean-aihub-learning-2
  
  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: 2.9945
  - Wer: 0.9533
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 0.99  | 35   | 46.3840         | 1.0    |
  | No log        | 1.99  | 70   | 26.0949         | 1.0    |
  | 37.1581       | 2.99  | 105  | 19.0168         | 1.0    |
  | 37.1581       | 3.99  | 140  | 13.3294         | 1.0    |
  | 37.1581       | 4.99  | 175  | 7.9410          | 1.0    |
  | 12.5054       | 5.99  | 210  | 5.0323          | 1.0    |
  | 12.5054       | 6.99  | 245  | 4.6242          | 1.0    |
  | 12.5054       | 7.99  | 280  | 4.6206          | 1.0    |
  | 4.8394        | 8.99  | 315  | 4.5820          | 1.0    |
  | 4.8394        | 9.99  | 350  | 4.5629          | 1.0    |
  | 4.8394        | 10.99 | 385  | 4.5385          | 1.0    |
  | 4.6489        | 11.99 | 420  | 4.5627          | 1.0    |
  | 4.6489        | 12.99 | 455  | 4.5276          | 1.0    |
  | 4.6489        | 13.99 | 490  | 4.5292          | 1.0    |
  | 4.5654        | 14.99 | 525  | 4.5179          | 1.0    |
  | 4.5654        | 15.99 | 560  | 4.4928          | 1.0    |
  | 4.5654        | 16.99 | 595  | 4.4791          | 1.0    |
  | 4.521         | 17.99 | 630  | 4.4649          | 1.0    |
  | 4.521         | 18.99 | 665  | 4.4588          | 1.0    |
  | 4.3529        | 19.99 | 700  | 4.3632          | 1.0    |
  | 4.3529        | 20.99 | 735  | 4.2990          | 1.0    |
  | 4.3529        | 21.99 | 770  | 4.2326          | 0.9988 |
  | 4.1301        | 22.99 | 805  | 4.0843          | 1.0    |
  | 4.1301        | 23.99 | 840  | 3.9784          | 0.9975 |
  | 4.1301        | 24.99 | 875  | 3.7876          | 1.0    |
  | 3.7047        | 25.99 | 910  | 3.6109          | 0.9988 |
  | 3.7047        | 26.99 | 945  | 3.4049          | 0.9828 |
  | 3.7047        | 27.99 | 980  | 3.1913          | 0.9606 |
  | 3.006         | 28.99 | 1015 | 3.0567          | 0.9508 |
  | 3.006         | 29.99 | 1050 | 2.9945          | 0.9533 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  