readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: korean-aihub-learning-math-16batch
    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-math-16batch
  
  This model is a fine-tuned version of [kresnik/wav2vec2-large-xlsr-korean](https://huggingface.co/kresnik/wav2vec2-large-xlsr-korean) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1497
  - Wer: 0.5260
  
  ## 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: 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
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.0   | 20   | 32.0718         | 1.0    |
  | No log        | 2.0   | 40   | 24.7403         | 1.0808 |
  | No log        | 3.0   | 60   | 5.8389          | 1.0    |
  | No log        | 4.0   | 80   | 4.8543          | 1.0    |
  | 19.6583       | 5.0   | 100  | 4.4453          | 1.0    |
  | 19.6583       | 6.0   | 120  | 4.3923          | 1.0    |
  | 19.6583       | 7.0   | 140  | 4.2902          | 1.0    |
  | 19.6583       | 8.0   | 160  | 3.9026          | 0.9959 |
  | 19.6583       | 9.0   | 180  | 3.0616          | 0.9740 |
  | 3.7358        | 10.0  | 200  | 2.2049          | 0.8534 |
  | 3.7358        | 11.0  | 220  | 1.6666          | 0.7288 |
  | 3.7358        | 12.0  | 240  | 1.4123          | 0.6603 |
  | 3.7358        | 13.0  | 260  | 1.3113          | 0.6164 |
  | 3.7358        | 14.0  | 280  | 1.2269          | 0.6356 |
  | 0.8398        | 15.0  | 300  | 1.2349          | 0.5945 |
  | 0.8398        | 16.0  | 320  | 1.1970          | 0.5658 |
  | 0.8398        | 17.0  | 340  | 1.2144          | 0.5562 |
  | 0.8398        | 18.0  | 360  | 1.2551          | 0.5658 |
  | 0.8398        | 19.0  | 380  | 1.1971          | 0.5493 |
  | 0.2649        | 20.0  | 400  | 1.1967          | 0.5247 |
  | 0.2649        | 21.0  | 420  | 1.2796          | 0.5849 |
  | 0.2649        | 22.0  | 440  | 1.2156          | 0.5521 |
  | 0.2649        | 23.0  | 460  | 1.2118          | 0.5425 |
  | 0.2649        | 24.0  | 480  | 1.1637          | 0.5384 |
  | 0.1801        | 25.0  | 500  | 1.1846          | 0.5562 |
  | 0.1801        | 26.0  | 520  | 1.1927          | 0.5534 |
  | 0.1801        | 27.0  | 540  | 1.2015          | 0.5384 |
  | 0.1801        | 28.0  | 560  | 1.2077          | 0.5397 |
  | 0.1801        | 29.0  | 580  | 1.1554          | 0.5260 |
  | 0.1364        | 30.0  | 600  | 1.1497          | 0.5260 |
  
  
  ### Framework versions
  
  - Transformers 4.22.0.dev0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  