readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - zeroth_korean
  model-index:
  - name: wav2vec2-large-xlsr-korean-demo3
    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-demo3
  
  This model is a fine-tuned version of [NX2411/wav2vec2-large-xlsr-korean-demo-no-LM](https://huggingface.co/NX2411/wav2vec2-large-xlsr-korean-demo-no-LM) on the zeroth_korean dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8265
  - Wer: 0.5090
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.6157        | 2.6   | 400  | 0.6686          | 0.6386 |
  | 0.4643        | 5.19  | 800  | 0.7036          | 0.6086 |
  | 0.3038        | 7.79  | 1200 | 0.6960          | 0.5817 |
  | 0.2229        | 10.39 | 1600 | 0.7358          | 0.5571 |
  | 0.178         | 12.99 | 2000 | 0.8221          | 0.5636 |
  | 0.153         | 15.58 | 2400 | 0.8575          | 0.5691 |
  | 0.129         | 18.18 | 2800 | 0.7809          | 0.5297 |
  | 0.1141        | 20.78 | 3200 | 0.8077          | 0.5441 |
  | 0.0994        | 23.38 | 3600 | 0.8087          | 0.5209 |
  | 0.0917        | 25.97 | 4000 | 0.8176          | 0.5149 |
  | 0.0823        | 28.57 | 4400 | 0.8265          | 0.5090 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  