readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-large-xls-r-300m-slowenian-with-lm
    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-slowenian-with-lm
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3935
  - Wer: 0.3480
  
  ## 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: 0.0001
  - train_batch_size: 32
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 50
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 7.9937        | 2.5   | 100  | 3.1565          | 1.0    |
  | 3.0466        | 5.0   | 200  | 3.0009          | 0.9992 |
  | 2.9708        | 7.5   | 300  | 2.9494          | 0.9992 |
  | 2.0519        | 10.0  | 400  | 0.8874          | 0.7290 |
  | 0.5773        | 12.5  | 500  | 0.5258          | 0.5037 |
  | 0.3427        | 15.0  | 600  | 0.4767          | 0.4649 |
  | 0.2612        | 17.5  | 700  | 0.4549          | 0.4209 |
  | 0.212         | 20.0  | 800  | 0.4294          | 0.3860 |
  | 0.1748        | 22.5  | 900  | 0.4085          | 0.3769 |
  | 0.1587        | 25.0  | 1000 | 0.4017          | 0.3673 |
  | 0.1435        | 27.5  | 1100 | 0.3927          | 0.3538 |
  | 0.1314        | 30.0  | 1200 | 0.3935          | 0.3480 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.9.0+cu111
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  