readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-300m-greek
    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-large-xls-r-300m-greek
  
  This model was trained from scratch on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4823
  - Wer: 0.3338
  
  ## 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: 3e-05
  - 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
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.0106        | 1.72  | 200  | 0.5519          | 0.3537 |
  | 0.0249        | 3.45  | 400  | 0.5174          | 0.3465 |
  | 0.0206        | 5.17  | 600  | 0.4721          | 0.3323 |
  | 0.0221        | 6.89  | 800  | 0.4652          | 0.3373 |
  | 0.0204        | 8.62  | 1000 | 0.4883          | 0.3389 |
  | 0.0192        | 10.34 | 1200 | 0.4785          | 0.3389 |
  | 0.0186        | 12.07 | 1400 | 0.4789          | 0.3378 |
  | 0.0172        | 13.79 | 1600 | 0.4915          | 0.3347 |
  | 0.0184        | 15.52 | 1800 | 0.4759          | 0.3440 |
  | 0.0168        | 17.24 | 2000 | 0.4891          | 0.3371 |
  | 0.0155        | 18.96 | 2200 | 0.4928          | 0.3394 |
  | 0.0146        | 20.69 | 2400 | 0.4834          | 0.3357 |
  | 0.0146        | 22.41 | 2600 | 0.4814          | 0.3362 |
  | 0.0151        | 24.14 | 2800 | 0.4791          | 0.3345 |
  | 0.0136        | 25.86 | 3000 | 0.4825          | 0.3356 |
  | 0.0136        | 27.58 | 3200 | 0.4850          | 0.3351 |
  | 0.0127        | 29.31 | 3400 | 0.4823          | 0.3338 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  