readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-300m-tr-colab
    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-tr-colab
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4121
  - Wer: 0.3112
  
  ## 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
  - distributed_type: multi-GPU
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 4.1868        | 1.83  | 400  | 0.9812          | 0.8398 |
  | 0.691         | 3.67  | 800  | 0.5571          | 0.6298 |
  | 0.3555        | 5.5   | 1200 | 0.4676          | 0.4779 |
  | 0.2451        | 7.34  | 1600 | 0.4572          | 0.4541 |
  | 0.1844        | 9.17  | 2000 | 0.4743          | 0.4389 |
  | 0.1541        | 11.01 | 2400 | 0.4583          | 0.4300 |
  | 0.1277        | 12.84 | 2800 | 0.4565          | 0.3950 |
  | 0.1122        | 14.68 | 3200 | 0.4761          | 0.4087 |
  | 0.0975        | 16.51 | 3600 | 0.4654          | 0.3786 |
  | 0.0861        | 18.35 | 4000 | 0.4503          | 0.3667 |
  | 0.0775        | 20.18 | 4400 | 0.4600          | 0.3581 |
  | 0.0666        | 22.02 | 4800 | 0.4350          | 0.3504 |
  | 0.0627        | 23.85 | 5200 | 0.4211          | 0.3349 |
  | 0.0558        | 25.69 | 5600 | 0.4390          | 0.3333 |
  | 0.0459        | 27.52 | 6000 | 0.4218          | 0.3185 |
  | 0.0439        | 29.36 | 6400 | 0.4121          | 0.3112 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  