readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-burak-new-300-v2-3
    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-v2-3
  
  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: 0.2910
  - Wer: 0.2712
  
  ## 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: 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: 71
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 7.5554        | 4.9   | 500  | 3.1912          | 1.0    |
  | 3.1116        | 9.8   | 1000 | 2.5931          | 1.0    |
  | 1.291         | 14.71 | 1500 | 0.4394          | 0.5575 |
  | 0.6214        | 19.61 | 2000 | 0.3243          | 0.4370 |
  | 0.4501        | 24.51 | 2500 | 0.2890          | 0.3517 |
  | 0.3659        | 29.41 | 3000 | 0.2809          | 0.3310 |
  | 0.3065        | 34.31 | 3500 | 0.2882          | 0.3076 |
  | 0.2739        | 39.22 | 4000 | 0.2632          | 0.2870 |
  | 0.2516        | 44.12 | 4500 | 0.2872          | 0.2897 |
  | 0.2316        | 49.02 | 5000 | 0.2875          | 0.2767 |
  | 0.2159        | 53.92 | 5500 | 0.2953          | 0.2746 |
  | 0.1957        | 58.82 | 6000 | 0.2955          | 0.2787 |
  | 0.1997        | 63.73 | 6500 | 0.2963          | 0.2822 |
  | 0.1852        | 68.63 | 7000 | 0.2910          | 0.2712 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  