readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
    name: wav2vec2-xlsr-vorarlbergerisch
  ---
  
  <!-- 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-xlsr-vorarlbergerisch
  
  This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-german](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-german) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.3193
  - Wer: 0.3235
  
  ## 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: 16
  - eval_batch_size: 8
  - 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
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 62
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 15.6717       | 3.83  | 100  | 3.0247          | 1.0    |
  | 2.485         | 7.68  | 200  | 1.5937          | 0.9046 |
  | 0.784         | 11.53 | 300  | 1.2664          | 0.5    |
  | 0.3689        | 15.38 | 400  | 1.2046          | 0.4696 |
  | 0.2618        | 19.23 | 500  | 1.1289          | 0.4155 |
  | 0.2088        | 23.08 | 600  | 0.9339          | 0.3623 |
  | 0.1388        | 26.91 | 700  | 1.1448          | 0.3573 |
  | 0.1042        | 30.75 | 800  | 1.1411          | 0.3606 |
  | 0.0784        | 34.6  | 900  | 1.2046          | 0.3547 |
  | 0.0607        | 38.45 | 1000 | 1.2243          | 0.3488 |
  | 0.0459        | 42.3  | 1100 | 1.2387          | 0.3226 |
  | 0.0273        | 46.15 | 1200 | 1.2123          | 0.3387 |
  | 0.0195        | 49.98 | 1300 | 1.2232          | 0.3345 |
  | 0.0188        | 53.83 | 1400 | 1.2656          | 0.3235 |
  | 0.0132        | 57.68 | 1500 | 1.3377          | 0.3285 |
  | 0.0089        | 61.53 | 1600 | 1.3193          | 0.3235 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  