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-stream
    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-stream
  
  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: 0.3519
  - Wer: 0.2927
  - Cer: 0.0694
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
  | 0.6768        | 9.01  | 500  | 0.4220          | 0.5143 | 0.1235 |
  | 0.3801        | 19.01 | 1000 | 0.3303          | 0.4403 | 0.1055 |
  | 0.3616        | 29.0  | 1500 | 0.3540          | 0.3716 | 0.0878 |
  | 0.2334        | 39.0  | 2000 | 0.3666          | 0.3671 | 0.0842 |
  | 0.3141        | 49.0  | 2500 | 0.3407          | 0.3373 | 0.0819 |
  | 0.1926        | 58.01 | 3000 | 0.3886          | 0.3520 | 0.0867 |
  | 0.1372        | 68.01 | 3500 | 0.3415          | 0.3189 | 0.0743 |
  | 0.091         | 78.0  | 4000 | 0.3750          | 0.3164 | 0.0757 |
  | 0.0893        | 88.0  | 4500 | 0.3559          | 0.2968 | 0.0712 |
  | 0.095         | 98.0  | 5000 | 0.3519          | 0.2927 | 0.0694 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.2
  - Datasets 1.18.2
  - Tokenizers 0.10.3
  