readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: wav2vec2-burak-new-300-v2-7
    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-v2-7
  
  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: 0.3394
  - Wer: 0.2306
  
  ## 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    |
  |:-------------:|:------:|:----:|:---------------:|:------:|
  | 5.3306        | 9.43   | 500  | 2.8304          | 1.0    |
  | 0.9789        | 18.87  | 1000 | 0.3443          | 0.4136 |
  | 0.3622        | 28.3   | 1500 | 0.3110          | 0.3235 |
  | 0.2535        | 37.74  | 2000 | 0.3166          | 0.3014 |
  | 0.1985        | 47.17  | 2500 | 0.3247          | 0.2980 |
  | 0.1673        | 56.6   | 3000 | 0.3082          | 0.2608 |
  | 0.1435        | 66.04  | 3500 | 0.3155          | 0.2615 |
  | 0.1281        | 75.47  | 4000 | 0.3480          | 0.2636 |
  | 0.1164        | 84.91  | 4500 | 0.3459          | 0.2560 |
  | 0.1055        | 94.34  | 5000 | 0.3330          | 0.2505 |
  | 0.0949        | 103.77 | 5500 | 0.3522          | 0.2436 |
  | 0.0891        | 113.21 | 6000 | 0.3511          | 0.2381 |
  | 0.0814        | 122.64 | 6500 | 0.3365          | 0.2347 |
  | 0.0785        | 132.08 | 7000 | 0.3426          | 0.2374 |
  | 0.0722        | 141.51 | 7500 | 0.3483          | 0.2312 |
  | 0.0704        | 150.94 | 8000 | 0.3394          | 0.2306 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  