readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
    name: wav2vec2-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-vorarlbergerisch
  
  This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.9241
  - Wer: 0.4358
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 12.6837       | 3.83  | 100  | 3.7188          | 1.0    |
  | 3.33          | 7.68  | 200  | 3.0620          | 1.0    |
  | 2.9508        | 11.53 | 300  | 2.5915          | 1.0101 |
  | 1.8954        | 15.38 | 400  | 1.6930          | 0.8243 |
  | 1.231         | 19.23 | 500  | 1.7179          | 0.7551 |
  | 0.9862        | 23.08 | 600  | 1.5237          | 0.6529 |
  | 0.7353        | 26.91 | 700  | 1.5119          | 0.5921 |
  | 0.5368        | 30.75 | 800  | 1.5011          | 0.5574 |
  | 0.4448        | 34.6  | 900  | 1.5334          | 0.5363 |
  | 0.3278        | 38.45 | 1000 | 1.7125          | 0.5144 |
  | 0.2575        | 42.3  | 1100 | 1.6529          | 0.4958 |
  | 0.1966        | 46.15 | 1200 | 1.7670          | 0.4848 |
  | 0.1552        | 49.98 | 1300 | 1.7586          | 0.4620 |
  | 0.1118        | 53.83 | 1400 | 1.7912          | 0.4417 |
  | 0.0847        | 57.68 | 1500 | 1.8709          | 0.4443 |
  | 0.0654        | 61.53 | 1600 | 1.9241          | 0.4358 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  