readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: wav2vec2-burak-new-300-v2-5
    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-v2-5
  
  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: 0.2833
  - Wer: 0.2168
  
  ## 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: 141
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer    |
  |:-------------:|:------:|:----:|:---------------:|:------:|
  | 6.3785        | 9.8    | 500  | 3.1380          | 1.0    |
  | 1.863         | 19.6   | 1000 | 0.3638          | 0.4659 |
  | 0.524         | 29.41  | 1500 | 0.2742          | 0.3379 |
  | 0.3581        | 39.21  | 2000 | 0.2746          | 0.3049 |
  | 0.2783        | 49.02  | 2500 | 0.2559          | 0.2877 |
  | 0.2378        | 58.82  | 3000 | 0.2613          | 0.2732 |
  | 0.2062        | 68.62  | 3500 | 0.2499          | 0.2602 |
  | 0.1849        | 78.43  | 4000 | 0.2809          | 0.2485 |
  | 0.1663        | 88.23  | 4500 | 0.2768          | 0.2429 |
  | 0.1526        | 98.04  | 5000 | 0.2767          | 0.2319 |
  | 0.1434        | 107.84 | 5500 | 0.2886          | 0.2285 |
  | 0.1338        | 117.64 | 6000 | 0.2808          | 0.2257 |
  | 0.1313        | 127.45 | 6500 | 0.2835          | 0.2106 |
  | 0.1281        | 137.25 | 7000 | 0.2833          | 0.2168 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  