readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-53h-turkish-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-53h-turkish-colab
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4135
  - Wer: 0.3247
  
  ## 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: 32
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 9.4875        | 0.92  | 100  | 3.5328          | 1.0    |
  | 3.1866        | 1.83  | 200  | 3.0955          | 1.0    |
  | 2.027         | 2.75  | 300  | 0.9002          | 0.7685 |
  | 0.7285        | 3.67  | 400  | 0.6279          | 0.6693 |
  | 0.4693        | 4.59  | 500  | 0.5672          | 0.5643 |
  | 0.3615        | 5.5   | 600  | 0.4995          | 0.5094 |
  | 0.2846        | 6.42  | 700  | 0.4561          | 0.4797 |
  | 0.2253        | 7.34  | 800  | 0.4742          | 0.4675 |
  | 0.2004        | 8.26  | 900  | 0.4462          | 0.4345 |
  | 0.173         | 9.17  | 1000 | 0.4688          | 0.4333 |
  | 0.1547        | 10.09 | 1100 | 0.4429          | 0.4206 |
  | 0.1444        | 11.01 | 1200 | 0.4662          | 0.4144 |
  | 0.1274        | 11.93 | 1300 | 0.4675          | 0.4213 |
  | 0.1164        | 12.84 | 1400 | 0.4947          | 0.4073 |
  | 0.1081        | 13.76 | 1500 | 0.4223          | 0.3915 |
  | 0.1025        | 14.68 | 1600 | 0.4493          | 0.3912 |
  | 0.0944        | 15.6  | 1700 | 0.4527          | 0.3848 |
  | 0.0943        | 16.51 | 1800 | 0.4288          | 0.3810 |
  | 0.0885        | 17.43 | 1900 | 0.4313          | 0.3670 |
  | 0.0781        | 18.35 | 2000 | 0.4729          | 0.3790 |
  | 0.0828        | 19.27 | 2100 | 0.4560          | 0.3651 |
  | 0.0753        | 20.18 | 2200 | 0.4478          | 0.3599 |
  | 0.0702        | 21.1  | 2300 | 0.4518          | 0.3595 |
  | 0.0666        | 22.02 | 2400 | 0.4080          | 0.3489 |
  | 0.0661        | 22.94 | 2500 | 0.4414          | 0.3507 |
  | 0.0607        | 23.85 | 2600 | 0.4209          | 0.3538 |
  | 0.058         | 24.77 | 2700 | 0.4302          | 0.3382 |
  | 0.0596        | 25.69 | 2800 | 0.3939          | 0.3328 |
  | 0.052         | 26.61 | 2900 | 0.4374          | 0.3311 |
  | 0.0473        | 27.52 | 3000 | 0.4406          | 0.3363 |
  | 0.0483        | 28.44 | 3100 | 0.4272          | 0.3286 |
  | 0.049         | 29.36 | 3200 | 0.4189          | 0.3257 |
  | 0.0433        | 30.28 | 3300 | 0.4242          | 0.3229 |
  | 0.0438        | 31.19 | 3400 | 0.4135          | 0.3247 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  