readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: wav2vec2-burak-new-300-v2-8
    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-v2-8
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2841
  - Wer: 0.2120
  
  ## 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: 0.0001
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 151
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer    |
  |:-------------:|:------:|:----:|:---------------:|:------:|
  | 6.0739        | 9.43   | 500  | 3.1506          | 1.0    |
  | 1.6652        | 18.87  | 1000 | 0.3396          | 0.4136 |
  | 0.4505        | 28.3   | 1500 | 0.2632          | 0.3138 |
  | 0.3115        | 37.74  | 2000 | 0.2536          | 0.2849 |
  | 0.2421        | 47.17  | 2500 | 0.2674          | 0.2588 |
  | 0.203         | 56.6   | 3000 | 0.2552          | 0.2471 |
  | 0.181         | 66.04  | 3500 | 0.2636          | 0.2595 |
  | 0.1581        | 75.47  | 4000 | 0.2527          | 0.2416 |
  | 0.1453        | 84.91  | 4500 | 0.2773          | 0.2257 |
  | 0.1305        | 94.34  | 5000 | 0.2825          | 0.2257 |
  | 0.1244        | 103.77 | 5500 | 0.2754          | 0.2312 |
  | 0.1127        | 113.21 | 6000 | 0.2772          | 0.2223 |
  | 0.1094        | 122.64 | 6500 | 0.2720          | 0.2223 |
  | 0.1033        | 132.08 | 7000 | 0.2863          | 0.2202 |
  | 0.099         | 141.51 | 7500 | 0.2853          | 0.2140 |
  | 0.0972        | 150.94 | 8000 | 0.2841          | 0.2120 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  