readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: wav2vec2-burak-new-300-v2-8-medium
    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-medium
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4311
  - Wer: 0.2602
  
  ## 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: 0.0002
  - 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    |
  |:-------------:|:------:|:----:|:---------------:|:------:|
  | 2.7459        | 9.43   | 500  | 0.3843          | 0.4597 |
  | 0.579         | 18.87  | 1000 | 0.3006          | 0.3668 |
  | 0.2662        | 28.3   | 1500 | 0.3760          | 0.3503 |
  | 0.1936        | 37.74  | 2000 | 0.3631          | 0.3214 |
  | 0.157         | 47.17  | 2500 | 0.3838          | 0.3063 |
  | 0.1307        | 56.6   | 3000 | 0.3671          | 0.3056 |
  | 0.1138        | 66.04  | 3500 | 0.3700          | 0.2959 |
  | 0.1002        | 75.47  | 4000 | 0.4164          | 0.3014 |
  | 0.0874        | 84.91  | 4500 | 0.4001          | 0.2973 |
  | 0.0791        | 94.34  | 5000 | 0.3883          | 0.2911 |
  | 0.0667        | 103.77 | 5500 | 0.4220          | 0.2780 |
  | 0.0581        | 113.21 | 6000 | 0.4163          | 0.2670 |
  | 0.0506        | 122.64 | 6500 | 0.4065          | 0.2753 |
  | 0.043         | 132.08 | 7000 | 0.4279          | 0.2643 |
  | 0.0386        | 141.51 | 7500 | 0.4284          | 0.2650 |
  | 0.0341        | 150.94 | 8000 | 0.4311          | 0.2602 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  