readme: ---
  language:
  - tr
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-common_voice-tr-demo
    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-common_voice-tr-demo
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the COMMON_VOICE - TR dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5682
  - Wer: 0.5739
  
  ## 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: 0.0003
  - train_batch_size: 64
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 15.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 3.69  | 100  | 3.5365          | 1.0    |
  | No log        | 7.4   | 200  | 2.9341          | 0.9999 |
  | No log        | 11.11 | 300  | 0.6994          | 0.6841 |
  | No log        | 14.8  | 400  | 0.5623          | 0.5792 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.6.1
  - Tokenizers 0.12.1
  