readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: wav2vec2-burak-new-300-v2-6
    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-v2-6
  
  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: 0.3074
  - Wer: 0.2340
  
  ## 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    |
  |:-------------:|:------:|:----:|:---------------:|:------:|
  | 6.3136        | 9.61   | 500  | 3.1262          | 1.0    |
  | 1.8247        | 19.23  | 1000 | 0.4049          | 0.5065 |
  | 0.5387        | 28.83  | 1500 | 0.2828          | 0.3462 |
  | 0.3713        | 38.45  | 2000 | 0.2761          | 0.3125 |
  | 0.293         | 48.08  | 2500 | 0.2872          | 0.3001 |
  | 0.2436        | 57.68  | 3000 | 0.2912          | 0.2904 |
  | 0.2116        | 67.3   | 3500 | 0.2910          | 0.2725 |
  | 0.1859        | 76.91  | 4000 | 0.2937          | 0.2533 |
  | 0.1731        | 86.53  | 4500 | 0.2985          | 0.2485 |
  | 0.1569        | 96.15  | 5000 | 0.3022          | 0.2409 |
  | 0.1471        | 105.76 | 5500 | 0.3070          | 0.2374 |
  | 0.1385        | 115.38 | 6000 | 0.2954          | 0.2429 |
  | 0.1289        | 124.99 | 6500 | 0.3016          | 0.2361 |
  | 0.1268        | 134.61 | 7000 | 0.3000          | 0.2368 |
  | 0.12          | 144.23 | 7500 | 0.3074          | 0.2340 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  