readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-burak-new-300-v2
    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-burak-new-300-v2
  
  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 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7018
  - Wer: 0.3641
  
  ## 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: 32
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 141
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer    |
  |:-------------:|:------:|:----:|:---------------:|:------:|
  | 4.2967        | 8.62   | 500  | 1.0561          | 0.8351 |
  | 0.5199        | 17.24  | 1000 | 0.6019          | 0.5054 |
  | 0.2249        | 25.86  | 1500 | 0.6036          | 0.4576 |
  | 0.1573        | 34.48  | 2000 | 0.6680          | 0.4532 |
  | 0.1301        | 43.1   | 2500 | 0.6823          | 0.4396 |
  | 0.1108        | 51.72  | 3000 | 0.6630          | 0.4263 |
  | 0.0941        | 60.34  | 3500 | 0.6574          | 0.4226 |
  | 0.0797        | 68.97  | 4000 | 0.6796          | 0.4174 |
  | 0.0689        | 77.59  | 4500 | 0.6426          | 0.4088 |
  | 0.0612        | 86.21  | 5000 | 0.6615          | 0.3949 |
  | 0.0528        | 94.83  | 5500 | 0.6769          | 0.3906 |
  | 0.0515        | 103.45 | 6000 | 0.6073          | 0.3827 |
  | 0.0394        | 112.07 | 6500 | 0.7099          | 0.3767 |
  | 0.0352        | 120.69 | 7000 | 0.7082          | 0.3688 |
  | 0.0324        | 129.31 | 7500 | 0.6939          | 0.3699 |
  | 0.028         | 137.93 | 8000 | 0.7018          | 0.3641 |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  