readme: ---
  license: cc0-1.0
  tags:
  - automatic-speech-recognition
  - NbAiLab/NPSC
  - generated_from_trainer
  model-index:
  - name: ''
    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. -->
  
  # 
  
  This model is a fine-tuned version of [KBLab/wav2vec2-large-voxrex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) on the NBAILAB/NPSC - 16K_MP3_NYNORSK dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4929
  - Wer: 0.1455
  
  ## 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: 4
  - eval_batch_size: 4
  - 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: 2000
  - num_epochs: 80.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 3.0168        | 0.54  | 500   | 3.0478          | 1.0    |
  | 2.8486        | 1.08  | 1000  | 2.7863          | 1.0    |
  | 1.0509        | 1.62  | 1500  | 0.8737          | 0.5449 |
  | 0.7873        | 2.16  | 2000  | 0.6718          | 0.4292 |
  | 0.6987        | 2.7   | 2500  | 0.5497          | 0.3589 |
  | 0.5548        | 3.24  | 3000  | 0.4841          | 0.3145 |
  | 0.5421        | 3.78  | 3500  | 0.4569          | 0.2927 |
  | 0.4416        | 4.31  | 4000  | 0.4702          | 0.2822 |
  | 0.4388        | 4.85  | 4500  | 0.4145          | 0.2641 |
  | 0.4011        | 5.39  | 5000  | 0.4033          | 0.2565 |
  | 0.3959        | 5.93  | 5500  | 0.4127          | 0.2450 |
  | 0.3643        | 6.47  | 6000  | 0.3972          | 0.2420 |
  | 0.3594        | 7.01  | 6500  | 0.3882          | 0.2392 |
  | 0.3315        | 7.55  | 7000  | 0.3714          | 0.2337 |
  | 0.3131        | 8.09  | 7500  | 0.3964          | 0.2313 |
  | 0.3192        | 8.63  | 8000  | 0.3711          | 0.2268 |
  | 0.2855        | 9.17  | 8500  | 0.3815          | 0.2293 |
  | 0.2756        | 9.71  | 9000  | 0.3653          | 0.2187 |
  | 0.248         | 10.25 | 9500  | 0.3929          | 0.2093 |
  | 0.2428        | 10.79 | 10000 | 0.3641          | 0.1986 |
  | 0.2412        | 11.33 | 10500 | 0.3687          | 0.1978 |
  | 0.2455        | 11.87 | 11000 | 0.3942          | 0.2005 |
  | 0.2181        | 12.41 | 11500 | 0.3611          | 0.1876 |
  | 0.2321        | 12.94 | 12000 | 0.3586          | 0.1940 |
  | 0.2132        | 13.48 | 12500 | 0.3904          | 0.1892 |
  | 0.2162        | 14.02 | 13000 | 0.3812          | 0.1867 |
  | 0.205         | 14.56 | 13500 | 0.3751          | 0.1839 |
  | 0.1757        | 15.1  | 14000 | 0.3722          | 0.1816 |
  | 0.1722        | 15.64 | 14500 | 0.3873          | 0.1793 |
  | 0.1862        | 16.18 | 15000 | 0.3924          | 0.1790 |
  | 0.1549        | 16.72 | 15500 | 0.3719          | 0.1782 |
  | 0.1616        | 17.26 | 16000 | 0.3570          | 0.1830 |
  | 0.1646        | 17.8  | 16500 | 0.3867          | 0.1839 |
  | 0.1541        | 18.34 | 17000 | 0.3944          | 0.1817 |
  | 0.165         | 18.88 | 17500 | 0.3909          | 0.1806 |
  | 0.152         | 19.42 | 18000 | 0.3883          | 0.1766 |
  | 0.1532        | 19.96 | 18500 | 0.3732          | 0.1783 |
  | 0.1498        | 20.5  | 19000 | 0.3931          | 0.1713 |
  | 0.1424        | 21.04 | 19500 | 0.4205          | 0.1730 |
  | 0.1394        | 21.57 | 20000 | 0.4291          | 0.1710 |
  | 0.1407        | 22.11 | 20500 | 0.4239          | 0.1757 |
  | 0.1275        | 22.65 | 21000 | 0.4171          | 0.1719 |
  | 0.1262        | 23.19 | 21500 | 0.4346          | 0.1706 |
  | 0.1301        | 23.73 | 22000 | 0.4281          | 0.1650 |
  | 0.1342        | 24.27 | 22500 | 0.4469          | 0.1680 |
  | 0.1249        | 24.81 | 23000 | 0.4297          | 0.1709 |
  | 0.1143        | 25.35 | 23500 | 0.4130          | 0.1665 |
  | 0.1121        | 25.89 | 24000 | 0.4458          | 0.1633 |
  | 0.1206        | 26.43 | 24500 | 0.4597          | 0.1663 |
  | 0.1142        | 26.97 | 25000 | 0.3961          | 0.1726 |
  | 0.1025        | 27.51 | 25500 | 0.3985          | 0.1629 |
  | 0.0961        | 28.05 | 26000 | 0.4002          | 0.1629 |
  | 0.1253        | 28.59 | 26500 | 0.4256          | 0.1624 |
  | 0.1228        | 29.13 | 27000 | 0.4308          | 0.1653 |
  | 0.1034        | 29.67 | 27500 | 0.4354          | 0.1646 |
  | 0.0853        | 30.2  | 28000 | 0.4200          | 0.1588 |
  | 0.0936        | 30.74 | 28500 | 0.4748          | 0.1596 |
  | 0.1015        | 31.28 | 29000 | 0.4383          | 0.1651 |
  | 0.1           | 31.82 | 29500 | 0.4436          | 0.1659 |
  | 0.1087        | 32.36 | 30000 | 0.4121          | 0.1596 |
  | 0.1084        | 