readme: ---
  license: cc-by-nc-4.0
  tags:
  - generated_from_trainer
  model-index:
  - name: test_bug2
    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. -->
  
  # test_bug2
  
  This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vietnamese-250h](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2977
  - Wer: 0.1839
  
  ## 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: 4
  - 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: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.1568        | 0.27  | 50   | 0.2764          | 0.1985 |
  | 0.0979        | 0.53  | 100  | 0.2421          | 0.1813 |
  | 0.1018        | 0.8   | 150  | 0.2420          | 0.1809 |
  | 0.1011        | 1.07  | 200  | 0.2520          | 0.1992 |
  | 0.0947        | 1.34  | 250  | 0.2580          | 0.1885 |
  | 0.1077        | 1.6   | 300  | 0.2641          | 0.2001 |
  | 0.109         | 1.87  | 350  | 0.3196          | 0.2156 |
  | 0.1239        | 2.14  | 400  | 0.3298          | 0.2163 |
  | 0.1286        | 2.41  | 450  | 0.3392          | 0.2436 |
  | 0.1515        | 2.67  | 500  | 0.3821          | 0.2450 |
  | 0.157         | 2.94  | 550  | 0.3771          | 0.2521 |
  | 0.1296        | 3.21  | 600  | 0.3917          | 0.2541 |
  | 0.1351        | 3.48  | 650  | 0.3670          | 0.2366 |
  | 0.1387        | 3.74  | 700  | 0.3503          | 0.2347 |
  | 0.1336        | 4.01  | 750  | 0.4018          | 0.2627 |
  | 0.114         | 4.28  | 800  | 0.3699          | 0.2723 |
  | 0.1254        | 4.54  | 850  | 0.3395          | 0.2404 |
  | 0.119         | 4.81  | 900  | 0.3410          | 0.2340 |
  | 0.1           | 5.08  | 950  | 0.3302          | 0.2216 |
  | 0.0968        | 5.35  | 1000 | 0.3346          | 0.2255 |
  | 0.0965        | 5.61  | 1050 | 0.3144          | 0.2140 |
  | 0.0906        | 5.88  | 1100 | 0.3277          | 0.2109 |
  | 0.0968        | 6.15  | 1150 | 0.3300          | 0.2141 |
  | 0.0818        | 6.42  | 1200 | 0.3272          | 0.2085 |
  | 0.0836        | 6.68  | 1250 | 0.3177          | 0.2014 |
  | 0.0803        | 6.95  | 1300 | 0.3185          | 0.2005 |
  | 0.0727        | 7.22  | 1350 | 0.3110          | 0.1928 |
  | 0.0687        | 7.49  | 1400 | 0.3118          | 0.1965 |
  | 0.0698        | 7.75  | 1450 | 0.3170          | 0.1955 |
  | 0.0651        | 8.02  | 1500 | 0.3119          | 0.1929 |
  | 0.0648        | 8.29  | 1550 | 0.3058          | 0.1904 |
  | 0.0612        | 8.56  | 1600 | 0.3087          | 0.1935 |
  | 0.0578        | 8.82  | 1650 | 0.3076          | 0.1871 |
  | 0.0557        | 9.09  | 1700 | 0.3037          | 0.1862 |
  | 0.0542        | 9.36  | 1750 | 0.2990          | 0.1858 |
  | 0.0551        | 9.62  | 1800 | 0.2962          | 0.1837 |
  | 0.0514        | 9.89  | 1850 | 0.2977          | 0.1839 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0
  - Pytorch 1.13.1+cu116
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  