readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - zeroth_korean_asr
  model-index:
  - name: wav2vec2-large-xls-r-300m-zeroth
    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-xls-r-300m-zeroth
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the zeroth_korean_asr dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7052
  - Wer: 0.4621
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 15.1763       | 1.61  | 400  | 4.6768          | 1.0    |
  | 3.1779        | 3.21  | 800  | 1.6680          | 0.8752 |
  | 1.052         | 4.82  | 1200 | 0.9580          | 0.7332 |
  | 0.5412        | 6.42  | 1600 | 0.7752          | 0.5993 |
  | 0.3281        | 8.03  | 2000 | 0.7158          | 0.5615 |
  | 0.2312        | 9.64  | 2400 | 0.6975          | 0.5532 |
  | 0.2001        | 11.24 | 2800 | 0.7489          | 0.5677 |
  | 0.1587        | 12.85 | 3200 | 0.6954          | 0.5267 |
  | 0.1321        | 14.46 | 3600 | 0.7329          | 0.5371 |
  | 0.1178        | 16.06 | 4000 | 0.7534          | 0.5341 |
  | 0.103         | 17.67 | 4400 | 0.7046          | 0.5066 |
  | 0.0843        | 19.28 | 4800 | 0.7507          | 0.5028 |
  | 0.079         | 20.88 | 5200 | 0.7137          | 0.4886 |
  | 0.0647        | 22.49 | 5600 | 0.7170          | 0.4855 |
  | 0.0565        | 24.1  | 6000 | 0.7124          | 0.4781 |
  | 0.0487        | 25.7  | 6400 | 0.7043          | 0.4721 |
  | 0.0433        | 27.31 | 6800 | 0.7128          | 0.4557 |
  | 0.0379        | 28.91 | 7200 | 0.7052          | 0.4621 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  