readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-300m-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-300m-turkish-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: 0.7532
  - Wer: 0.4020
  
  ## 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: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 5.9542        | 1.96  | 400  | 1.5737          | 0.8827 |
  | 0.8596        | 3.92  | 800  | 0.7296          | 0.5696 |
  | 0.4729        | 5.88  | 1200 | 0.6004          | 0.4934 |
  | 0.3364        | 7.84  | 1600 | 0.5776          | 0.4656 |
  | 0.2684        | 9.8   | 2000 | 0.6178          | 0.4563 |
  | 0.2143        | 11.76 | 2400 | 0.6408          | 0.4690 |
  | 0.1744        | 13.72 | 2800 | 0.6704          | 0.4573 |
  | 0.1458        | 15.68 | 3200 | 0.7015          | 0.4484 |
  | 0.1201        | 17.65 | 3600 | 0.7151          | 0.4228 |
  | 0.104         | 19.61 | 4000 | 0.7123          | 0.4195 |
  | 0.0887        | 21.57 | 4400 | 0.7102          | 0.4234 |
  | 0.0807        | 23.53 | 4800 | 0.7561          | 0.4132 |
  | 0.0697        | 25.49 | 5200 | 0.7435          | 0.4075 |
  | 0.0611        | 27.45 | 5600 | 0.7465          | 0.4034 |
  | 0.0556        | 29.41 | 6000 | 0.7532          | 0.4020 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  