readme: ---
  language:
  - tr
  tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: hello_2b_3
    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. -->
  
  # hello_2b_3
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-2b](https://huggingface.co/facebook/wav2vec2-xls-r-2b) on the COMMON_VOICE - TR dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.5615
  - Wer: 0.9808
  
  ## 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: 5e-06
  - train_batch_size: 2
  - eval_batch_size: 8
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 2
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 32
  - total_eval_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 30.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.6389        | 0.92  | 100  | 3.6218          | 1.0    |
  | 1.6676        | 1.85  | 200  | 3.2655          | 1.0    |
  | 0.3067        | 2.77  | 300  | 3.2273          | 1.0    |
  | 0.1924        | 3.7   | 400  | 3.0238          | 0.9999 |
  | 0.1777        | 4.63  | 500  | 2.1606          | 0.9991 |
  | 0.1481        | 5.55  | 600  | 1.8742          | 0.9982 |
  | 0.1128        | 6.48  | 700  | 2.0114          | 0.9994 |
  | 0.1806        | 7.4   | 800  | 1.9032          | 0.9984 |
  | 0.0399        | 8.33  | 900  | 2.0556          | 0.9996 |
  | 0.0729        | 9.26  | 1000 | 2.0515          | 0.9987 |
  | 0.0847        | 10.18 | 1100 | 2.2121          | 0.9995 |
  | 0.0777        | 11.11 | 1200 | 1.7002          | 0.9923 |
  | 0.0476        | 12.04 | 1300 | 1.5262          | 0.9792 |
  | 0.0518        | 12.96 | 1400 | 1.5990          | 0.9832 |
  | 0.071         | 13.88 | 1500 | 1.6326          | 0.9875 |
  | 0.0333        | 14.81 | 1600 | 1.5955          | 0.9870 |
  | 0.0369        | 15.74 | 1700 | 1.5577          | 0.9832 |
  | 0.0689        | 16.66 | 1800 | 1.5415          | 0.9839 |
  | 0.0227        | 17.59 | 1900 | 1.5450          | 0.9878 |
  | 0.0472        | 18.51 | 2000 | 1.5642          | 0.9846 |
  | 0.0214        | 19.44 | 2100 | 1.6103          | 0.9846 |
  | 0.0289        | 20.37 | 2200 | 1.6467          | 0.9898 |
  | 0.0182        | 21.29 | 2300 | 1.5268          | 0.9780 |
  | 0.0439        | 22.22 | 2400 | 1.6001          | 0.9818 |
  | 0.06          | 23.15 | 2500 | 1.5481          | 0.9813 |
  | 0.0351        | 24.07 | 2600 | 1.5672          | 0.9820 |
  | 0.0198        | 24.99 | 2700 | 1.6303          | 0.9856 |
  | 0.0328        | 25.92 | 2800 | 1.5958          | 0.9831 |
  | 0.0245        | 26.85 | 2900 | 1.5745          | 0.9809 |
  | 0.0885        | 27.77 | 3000 | 1.5455          | 0.9809 |
  | 0.0224        | 28.7  | 3100 | 1.5378          | 0.9824 |
  | 0.0223        | 29.63 | 3200 | 1.5642          | 0.9810 |
  
  
  ### Framework versions
  
  - Transformers 4.13.0.dev0
  - Pytorch 1.10.0
  - Datasets 1.15.2.dev0
  - Tokenizers 0.10.3
  