readme: ---
  license: cc-by-nc-4.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-vi5
    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-vi5
  
  This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-large-vi-vlsp2020](https://huggingface.co/nguyenvulebinh/wav2vec2-large-vi-vlsp2020) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1632
  - Wer: 0.0714
  
  ## 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: 0.0001
  - train_batch_size: 1
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 4
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.1279        | 0.13  | 100  | 0.1495          | 0.0691 |
  | 0.1067        | 0.27  | 200  | 0.1407          | 0.0656 |
  | 0.1013        | 0.4   | 300  | 0.1352          | 0.0654 |
  | 0.1282        | 0.53  | 400  | 0.1468          | 0.0705 |
  | 0.1117        | 0.67  | 500  | 0.1658          | 0.0804 |
  | 0.1173        | 0.8   | 600  | 0.1485          | 0.0753 |
  | 0.1           | 0.94  | 700  | 0.1418          | 0.0699 |
  | 0.1029        | 1.07  | 800  | 0.1523          | 0.0715 |
  | 0.0823        | 1.2   | 900  | 0.1597          | 0.0731 |
  | 0.0893        | 1.34  | 1000 | 0.1441          | 0.0688 |
  | 0.0822        | 1.47  | 1100 | 0.1580          | 0.0711 |
  | 0.1077        | 1.6   | 1200 | 0.1664          | 0.0832 |
  | 0.0988        | 1.74  | 1300 | 0.1626          | 0.0744 |
  | 0.0777        | 1.87  | 1400 | 0.1498          | 0.0705 |
  | 0.0849        | 2.01  | 1500 | 0.1581          | 0.0711 |
  | 0.0647        | 2.14  | 1600 | 0.1636          | 0.0729 |
  | 0.0638        | 2.27  | 1700 | 0.1590          | 0.0750 |
  | 0.0674        | 2.41  | 1800 | 0.1627          | 0.0755 |
  | 0.0644        | 2.54  | 1900 | 0.1576          | 0.0746 |
  | 0.0666        | 2.67  | 2000 | 0.1569          | 0.0704 |
  | 0.0647        | 2.81  | 2100 | 0.1601          | 0.0693 |
  | 0.0769        | 2.94  | 2200 | 0.1595          | 0.0680 |
  | 0.0585        | 3.07  | 2300 | 0.1591          | 0.0718 |
  | 0.0515        | 3.21  | 2400 | 0.1628          | 0.0714 |
  | 0.068         | 3.34  | 2500 | 0.1549          | 0.0704 |
  | 0.0473        | 3.48  | 2600 | 0.1618          | 0.0694 |
  | 0.0545        | 3.61  | 2700 | 0.1539          | 0.0685 |
  | 0.049         | 3.74  | 2800 | 0.1546          | 0.0698 |
  | 0.0538        | 3.88  | 2900 | 0.1507          | 0.0698 |
  | 0.0452        | 4.01  | 3000 | 0.1516          | 0.0702 |
  | 0.0398        | 4.14  | 3100 | 0.1604          | 0.0723 |
  | 0.0539        | 4.28  | 3200 | 0.1587          | 0.0713 |
  | 0.0443        | 4.41  | 3300 | 0.1607          | 0.0718 |
  | 0.0405        | 4.55  | 3400 | 0.1626          | 0.0709 |
  | 0.038         | 4.68  | 3500 | 0.1623          | 0.0707 |
  | 0.0388        | 4.81  | 3600 | 0.1621          | 0.0726 |
  | 0.0418        | 4.95  | 3700 | 0.1632          | 0.0714 |
  
  
  ### Framework versions
  
  - Transformers 4.20.0
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  