readme: ---
  tags:
  - automatic-speech-recognition
  - gary109/AI_Light_Dance
  - generated_from_trainer
  model-index:
  - name: ai-light-dance_singing5_ft_wav2vec2-large-xlsr-53-5gram-v4-2-1
    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. -->
  
  # ai-light-dance_singing5_ft_wav2vec2-large-xlsr-53-5gram-v4-2-1
  
  This model is a fine-tuned version of [gary109/ai-light-dance_singing4_ft_wav2vec2-large-xlsr-53-5gram-v4-2-1](https://huggingface.co/gary109/ai-light-dance_singing4_ft_wav2vec2-large-xlsr-53-5gram-v4-2-1) on the GARY109/AI_LIGHT_DANCE - ONSET-SINGING5 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1732
  - Wer: 0.0831
  
  ## 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: 4e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 100
  - num_epochs: 50.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.4351        | 1.0   | 100  | 0.1948          | 0.0903 |
  | 0.4381        | 2.0   | 200  | 0.1961          | 0.0930 |
  | 0.441         | 3.0   | 300  | 0.1948          | 0.0957 |
  | 0.453         | 4.0   | 400  | 0.1971          | 0.0905 |
  | 0.4324        | 5.0   | 500  | 0.1823          | 0.0879 |
  | 0.4561        | 6.0   | 600  | 0.1934          | 0.0893 |
  | 0.4231        | 7.0   | 700  | 0.2088          | 0.0977 |
  | 0.4339        | 8.0   | 800  | 0.1924          | 0.0856 |
  | 0.4195        | 9.0   | 900  | 0.1835          | 0.0846 |
  | 0.4162        | 10.0  | 1000 | 0.1869          | 0.0908 |
  | 0.411         | 11.0  | 1100 | 0.1966          | 0.0950 |
  | 0.4034        | 12.0  | 1200 | 0.1890          | 0.0879 |
  | 0.4155        | 13.0  | 1300 | 0.1844          | 0.0915 |
  | 0.4123        | 14.0  | 1400 | 0.1849          | 0.0891 |
  | 0.4002        | 15.0  | 1500 | 0.1901          | 0.0902 |
  | 0.3983        | 16.0  | 1600 | 0.1879          | 0.0865 |
  | 0.3907        | 17.0  | 1700 | 0.1863          | 0.0856 |
  | 0.3969        | 18.0  | 1800 | 0.1773          | 0.0836 |
  | 0.3721        | 19.0  | 1900 | 0.1834          | 0.0890 |
  | 0.3987        | 20.0  | 2000 | 0.1817          | 0.0852 |
  | 0.3863        | 21.0  | 2100 | 0.1898          | 0.0914 |
  | 0.4052        | 22.0  | 2200 | 0.1882          | 0.0857 |
  | 0.3811        | 23.0  | 2300 | 0.1874          | 0.0856 |
  | 0.3791        | 24.0  | 2400 | 0.1932          | 0.0885 |
  | 0.3919        | 25.0  | 2500 | 0.1847          | 0.0815 |
  | 0.3891        | 26.0  | 2600 | 0.1850          | 0.0852 |
  | 0.3719        | 27.0  | 2700 | 0.1774          | 0.0820 |
  | 0.3791        | 28.0  | 2800 | 0.1756          | 0.0825 |
  | 0.3537        | 29.0  | 2900 | 0.1797          | 0.0844 |
  | 0.361         | 30.0  | 3000 | 0.1818          | 0.0834 |
  | 0.3619        | 31.0  | 3100 | 0.1747          | 0.0838 |
  | 0.3626        | 32.0  | 3200 | 0.1773          | 0.0844 |
  | 0.3632        | 33.0  | 3300 | 0.1775          | 0.0825 |
  | 0.3666        | 34.0  | 3400 | 0.1835          | 0.0859 |
  | 0.3581        | 35.0  | 3500 | 0.1859          | 0.0868 |
  | 0.3665        | 36.0  | 3600 | 0.1741          | 0.0849 |
  | 0.3495        | 37.0  | 3700 | 0.1790          | 0.0837 |
  | 0.3509        | 38.0  | 3800 | 0.1782          | 0.0841 |
  | 0.3621        | 39.0  | 3900 | 0.1759          | 0.0841 |
  | 0.3415        | 40.0  | 4000 | 0.1796          | 0.0851 |
  | 0.3508        | 41.0  | 4100 | 0.1777          | 0.0821 |
  | 0.3493        | 42.0  | 4200 | 0.1758          | 0.0829 |
  | 0.359         | 43.0  | 4300 | 0.1788          | 0.0848 |
  | 0.3438        | 44.0  | 4400 | 0.1782          | 0.0836 |
  | 0.3642        | 45.0  | 4500 | 0.1732          | 0.0831 |
  | 0.3456        | 46.0  | 4600 | 0.1768          | 0.0823 |
  | 0.3532        | 47.0  | 4700 | 0.1735          | 0.0834 |
  | 0.3448        | 48.0  | 4800 | 0.1755          | 0.0827 |
  | 0.3487        | 49.0  | 4900 | 0.1767          | 0.0833 |
  | 0.3427        | 50.0  | 5000 | 0.1774          | 0.0836 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0.dev0
  - Pytorch 1.9.1+cu102
  - Datasets 2.3.3.dev0
  - Tokenizers 0.12.1
  