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
    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
  
  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: 0.5806
  - Wer: 0.3998
  - Cer: 0.1053
  
  ## 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    |
  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
  | 0.5369        | 17.0   | 500  | 0.6021          | 0.6366 | 0.1727 |
  | 0.3542        | 34.0   | 1000 | 0.5265          | 0.4906 | 0.1278 |
  | 0.1866        | 51.0   | 1500 | 0.5805          | 0.4768 | 0.1261 |
  | 0.1674        | 68.01  | 2000 | 0.5336          | 0.4518 | 0.1186 |
  | 0.19          | 86.0   | 2500 | 0.5676          | 0.4427 | 0.1151 |
  | 0.0815        | 103.0  | 3000 | 0.5510          | 0.4268 | 0.1125 |
  | 0.0545        | 120.0  | 3500 | 0.5608          | 0.4175 | 0.1099 |
  | 0.0299        | 137.01 | 4000 | 0.5875          | 0.4222 | 0.1124 |
  | 0.0267        | 155.0  | 4500 | 0.5882          | 0.4026 | 0.1063 |
  | 0.025         | 172.0  | 5000 | 0.5806          | 0.3998 | 0.1053 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2
  - Datasets 1.18.2
  - Tokenizers 0.10.3
  