readme: ---
  language:
  - tr
  tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: hello_2b
    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
  
  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: 1.2725
  - Wer: 0.9531
  
  ## 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: 1e-05
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.1646        | 0.92  | 100  | 3.2106          | 1.0    |
  | 0.368         | 1.85  | 200  | 2.9963          | 1.0    |
  | 0.2252        | 2.77  | 300  | 2.8078          | 0.9999 |
  | 0.1546        | 3.7   | 400  | 2.3458          | 0.9996 |
  | 0.1468        | 4.63  | 500  | 2.0086          | 0.9986 |
  | 0.1261        | 5.55  | 600  | 1.8269          | 0.9985 |
  | 0.1206        | 6.48  | 700  | 1.7347          | 0.9956 |
  | 0.1959        | 7.4   | 800  | 1.6819          | 0.9955 |
  | 0.0502        | 8.33  | 900  | 1.6809          | 0.9965 |
  | 0.0811        | 9.26  | 1000 | 1.6674          | 0.9916 |
  | 0.0534        | 10.18 | 1100 | 1.5719          | 0.9898 |
  | 0.0402        | 11.11 | 1200 | 1.4620          | 0.9821 |
  | 0.057         | 12.04 | 1300 | 1.3015          | 0.9554 |
  | 0.0385        | 12.96 | 1400 | 1.3798          | 0.9600 |
  | 0.0422        | 13.88 | 1500 | 1.3538          | 0.9699 |
  | 0.014         | 14.81 | 1600 | 1.2507          | 0.9443 |
  | 0.0232        | 15.74 | 1700 | 1.3318          | 0.9465 |
  | 0.0554        | 16.66 | 1800 | 1.2784          | 0.9462 |
  | 0.0316        | 17.59 | 1900 | 1.2503          | 0.9481 |
  | 0.0524        | 18.51 | 2000 | 1.3920          | 0.9604 |
  | 0.0142        | 19.44 | 2100 | 1.4224          | 0.9698 |
  | 0.0288        | 20.37 | 2200 | 1.3475          | 0.9635 |
  | 0.0106        | 21.29 | 2300 | 1.2232          | 0.9264 |
  | 0.0396        | 22.22 | 2400 | 1.3323          | 0.9615 |
  | 0.0349        | 23.15 | 2500 | 1.2741          | 0.9587 |
  | 0.0121        | 24.07 | 2600 | 1.2671          | 0.9586 |
  | 0.0224        | 24.99 | 2700 | 1.3001          | 0.9611 |
  | 0.0449        | 25.92 | 2800 | 1.2777          | 0.9572 |
  | 0.0186        | 26.85 | 2900 | 1.2766          | 0.9607 |
  | 0.0365        | 27.77 | 3000 | 1.2935          | 0.9598 |
  | 0.0105        | 28.7  | 3100 | 1.2761          | 0.9588 |
  | 0.021         | 29.63 | 3200 | 1.2686          | 0.9528 |
  
  
  ### Framework versions
  
  - Transformers 4.13.0.dev0
  - Pytorch 1.10.0
  - Datasets 1.15.2.dev0
  - Tokenizers 0.10.3
  