readme: ---
  language:
  - nl
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-common_voice-nl-demo
    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-common_voice-nl-demo
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the COMMON_VOICE - NL dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3523
  - Wer: 0.2046
  
  ## 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: 4
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 15.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.0536        | 1.12  | 500  | 0.5349          | 0.4338 |
  | 0.2543        | 2.24  | 1000 | 0.3859          | 0.3029 |
  | 0.1472        | 3.36  | 1500 | 0.3471          | 0.2818 |
  | 0.1088        | 4.47  | 2000 | 0.3489          | 0.2731 |
  | 0.0855        | 5.59  | 2500 | 0.3582          | 0.2558 |
  | 0.0721        | 6.71  | 3000 | 0.3457          | 0.2471 |
  | 0.0653        | 7.83  | 3500 | 0.3299          | 0.2357 |
  | 0.0527        | 8.95  | 4000 | 0.3440          | 0.2334 |
  | 0.0444        | 10.07 | 4500 | 0.3417          | 0.2289 |
  | 0.0404        | 11.19 | 5000 | 0.3691          | 0.2204 |
  | 0.0345        | 12.3  | 5500 | 0.3453          | 0.2102 |
  | 0.0288        | 13.42 | 6000 | 0.3634          | 0.2089 |
  | 0.027         | 14.54 | 6500 | 0.3532          | 0.2044 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  