readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: korean-aihub-learning-math-8batch
    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-8batch
  
  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: 1.1867
  - Wer: 0.5315
  
  ## 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   | 33.1529         | 1.0    |
  | No log        | 2.0   | 40   | 28.0161         | 1.0    |
  | No log        | 3.0   | 60   | 8.7324          | 1.0    |
  | No log        | 4.0   | 80   | 4.9786          | 1.0    |
  | 21.6269       | 5.0   | 100  | 4.5335          | 1.0    |
  | 21.6269       | 6.0   | 120  | 4.4517          | 1.0    |
  | 21.6269       | 7.0   | 140  | 4.4068          | 1.0    |
  | 21.6269       | 8.0   | 160  | 4.3210          | 1.0    |
  | 21.6269       | 9.0   | 180  | 4.0041          | 0.9932 |
  | 4.1788        | 10.0  | 200  | 3.0921          | 0.9712 |
  | 4.1788        | 11.0  | 220  | 2.1650          | 0.8603 |
  | 4.1788        | 12.0  | 240  | 1.6135          | 0.7192 |
  | 4.1788        | 13.0  | 260  | 1.3842          | 0.6466 |
  | 4.1788        | 14.0  | 280  | 1.2872          | 0.5918 |
  | 1.205         | 15.0  | 300  | 1.2234          | 0.5808 |
  | 1.205         | 16.0  | 320  | 1.2694          | 0.6    |
  | 1.205         | 17.0  | 340  | 1.2287          | 0.5575 |
  | 1.205         | 18.0  | 360  | 1.1776          | 0.5877 |
  | 1.205         | 19.0  | 380  | 1.2418          | 0.5671 |
  | 0.2825        | 20.0  | 400  | 1.2469          | 0.5616 |
  | 0.2825        | 21.0  | 420  | 1.2203          | 0.5425 |
  | 0.2825        | 22.0  | 440  | 1.2270          | 0.5863 |
  | 0.2825        | 23.0  | 460  | 1.1930          | 0.5548 |
  | 0.2825        | 24.0  | 480  | 1.1242          | 0.5521 |
  | 0.1831        | 25.0  | 500  | 1.2245          | 0.5575 |
  | 0.1831        | 26.0  | 520  | 1.2276          | 0.5342 |
  | 0.1831        | 27.0  | 540  | 1.1641          | 0.5205 |
  | 0.1831        | 28.0  | 560  | 1.1727          | 0.5329 |
  | 0.1831        | 29.0  | 580  | 1.1885          | 0.5534 |
  | 0.14          | 30.0  | 600  | 1.1867          | 0.5315 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  