readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - automatic-speech-recognition
  - NbAiLab/NPSC
  - robust-speech-event
  - false
  - nb-NO
  - hf-asr-leaderboard
  datasets:
  - NbAiLab/NPSC
  language:
  - nb-NO
  model-index:
  - name: wav2vec2-large-voxrex-npsc-bokmaal
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: NPSC
        type: NbAiLab/NPSC
        args: 16K_mp3_bokmaal
      metrics:
      - name: "Test (Bokm\xE5l) WER"
        type: wer
        value: 0.07028972259374369
      - name: "Test (Bokm\xE5l) CER"
        type: cer
        value: 0.026870600821650645
  ---
  
  <!-- 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-voxrex-npsc-bokmaal
  
  This model was trained from scratch on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1311
  - Wer: 0.1038
  
  ## 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: 8.379967082059723e-06
  - train_batch_size: 16
  - eval_batch_size: 16
  - 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
  - num_epochs: 0.1
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.2127        | 0.32  | 500  | 0.1335          | 0.1047 |
  | 0.1976        | 0.64  | 1000 | 0.1309          | 0.1039 |
  | 0.1887        | 0.97  | 1500 | 0.1306          | 0.1040 |
  | 0.18          | 1.29  | 2000 | 0.1311          | 0.1038 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu113
  - Datasets 1.18.4.dev0
  - Tokenizers 0.11.0
  