readme: ---
  language:
  - tr
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-common_voice-tr-demo-dist
    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-common_voice-tr-demo-dist
  
  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 - TR dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3848
  - Wer: 0.3242
  
  ## 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: 4
  - eval_batch_size: 8
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 4
  - total_train_batch_size: 16
  - 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
  - num_epochs: 15.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.5279        | 0.46  | 100  | 3.6260          | 1.0    |
  | 3.1065        | 0.92  | 200  | 3.0854          | 0.9999 |
  | 1.4111        | 1.38  | 300  | 1.3343          | 0.8839 |
  | 0.8468        | 1.83  | 400  | 0.6920          | 0.6826 |
  | 0.6242        | 2.29  | 500  | 0.6001          | 0.5996 |
  | 0.4181        | 2.75  | 600  | 0.5655          | 0.5680 |
  | 0.4311        | 3.21  | 700  | 0.4478          | 0.5003 |
  | 0.3601        | 3.67  | 800  | 0.4548          | 0.5011 |
  | 0.2756        | 4.13  | 900  | 0.4444          | 0.4682 |
  | 0.2373        | 4.59  | 1000 | 0.4111          | 0.4432 |
  | 0.1831        | 5.05  | 1100 | 0.4178          | 0.4447 |
  | 0.2423        | 5.5   | 1200 | 0.3881          | 0.4277 |
  | 0.2128        | 5.96  | 1300 | 0.3865          | 0.4018 |
  | 0.1256        | 6.42  | 1400 | 0.3818          | 0.4137 |
  | 0.1038        | 6.88  | 1500 | 0.3739          | 0.3942 |
  | 0.1662        | 7.34  | 1600 | 0.3938          | 0.3929 |
  | 0.198         | 7.8   | 1700 | 0.3831          | 0.3837 |
  | 0.0728        | 8.26  | 1800 | 0.3910          | 0.3867 |
  | 0.123         | 8.72  | 1900 | 0.3722          | 0.3735 |
  | 0.0776        | 9.17  | 2000 | 0.3938          | 0.3725 |
  | 0.1597        | 9.63  | 2100 | 0.3786          | 0.3697 |
  | 0.1124        | 10.09 | 2200 | 0.3947          | 0.3590 |
  | 0.0965        | 10.55 | 2300 | 0.3952          | 0.3562 |
  | 0.0612        | 11.01 | 2400 | 0.3810          | 0.3476 |
  | 0.0764        | 11.47 | 2500 | 0.3734          | 0.3507 |
  | 0.0973        | 11.93 | 2600 | 0.3935          | 0.3472 |
  | 0.0649        | 12.39 | 2700 | 0.3672          | 0.3413 |
  | 0.0542        | 12.84 | 2800 | 0.3732          | 0.3369 |
  | 0.087         | 13.3  | 2900 | 0.3833          | 0.3458 |
  | 0.0196        | 13.76 | 3000 | 0.3761          | 0.3303 |
  | 0.0548        | 14.22 | 3100 | 0.3855          | 0.3274 |
  | 0.0577        | 14.68 | 3200 | 0.3893          | 0.3238 |
  
  
  ### Framework versions
  
  - Transformers 4.20.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  