readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-large-xlsr-korean-demo-colab_epoch15
    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_epoch15
  
  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: 0.4133
  - Wer: 0.3801
  
  ## 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: 15
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 16.9017       | 0.8   | 400  | 4.6273          | 1.0    |
  | 4.4633        | 1.6   | 800  | 4.4419          | 1.0    |
  | 4.2262        | 2.4   | 1200 | 3.8477          | 0.9994 |
  | 2.4402        | 3.21  | 1600 | 1.3564          | 0.8111 |
  | 1.3499        | 4.01  | 2000 | 0.9070          | 0.6664 |
  | 0.9922        | 4.81  | 2400 | 0.7496          | 0.6131 |
  | 0.8271        | 5.61  | 2800 | 0.6240          | 0.5408 |
  | 0.6918        | 6.41  | 3200 | 0.5506          | 0.5026 |
  | 0.6015        | 7.21  | 3600 | 0.5303          | 0.4935 |
  | 0.5435        | 8.02  | 4000 | 0.4951          | 0.4696 |
  | 0.4584        | 8.82  | 4400 | 0.4677          | 0.4432 |
  | 0.4258        | 9.62  | 4800 | 0.4602          | 0.4307 |
  | 0.3906        | 10.42 | 5200 | 0.4456          | 0.4195 |
  | 0.3481        | 11.22 | 5600 | 0.4265          | 0.4062 |
  | 0.3216        | 12.02 | 6000 | 0.4241          | 0.4046 |
  | 0.2908        | 12.83 | 6400 | 0.4106          | 0.3941 |
  | 0.2747        | 13.63 | 6800 | 0.4146          | 0.3855 |
  | 0.2633        | 14.43 | 7200 | 0.4133          | 0.3801 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.12.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  