readme: ---
  language:
  - tr
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
  model-index:
  - name: wav2vec2-xls-r-common_voice-tr-ft-500sh
    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-xls-r-common_voice-tr-ft-500sh
  
  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 - TR dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5794
  - Wer: 0.4009
  - Cer: 0.1032
  
  ## 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: 0.0005
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 4
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 64
  - total_eval_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 5000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    |
  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
  | 0.5288        | 17.0   | 500  | 0.5099          | 0.5426 | 0.1432 |
  | 0.2967        | 34.0   | 1000 | 0.5421          | 0.4746 | 0.1256 |
  | 0.2447        | 51.0   | 1500 | 0.5347          | 0.4831 | 0.1267 |
  | 0.122         | 68.01  | 2000 | 0.5854          | 0.4479 | 0.1161 |
  | 0.1035        | 86.0   | 2500 | 0.5597          | 0.4457 | 0.1166 |
  | 0.081         | 103.0  | 3000 | 0.5748          | 0.4250 | 0.1144 |
  | 0.0849        | 120.0  | 3500 | 0.5598          | 0.4337 | 0.1145 |
  | 0.0542        | 137.01 | 4000 | 0.5687          | 0.4223 | 0.1097 |
  | 0.0318        | 155.0  | 4500 | 0.5904          | 0.4057 | 0.1052 |
  | 0.0106        | 172.0  | 5000 | 0.5794          | 0.4009 | 0.1032 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2
  - Datasets 1.18.2
  - Tokenizers 0.10.3
  