readme: ---
  language:
  - tr
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
  - hf-asr-leaderboard
  - robust-speech-event
  - tr
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: Wav2Vec2 Base Turkish by Cahya
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 6.1
        type: mozilla-foundation/common_voice_7_0
        args: tr
      metrics:
      - name: Test WER
        type: wer
        value: 9.437
      - name: Test CER
        type: cer
        value: 3.325
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: tr
      metrics:
      - name: Test WER
        type: wer
        value: 8.147
      - name: Test CER
        type: cer
        value: 2.802
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: tr
      metrics:
      - name: Test WER
        type: wer
        value: 28.011
      - name: Test CER
        type: cer
        value: 10.66
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: tr
      metrics:
      - name: Test WER
        type: wer
        value: 33.62
  ---
        
  # 
  
  This model is a fine-tuned version of [cahya/wav2vec2-base-turkish-artificial-cv](https://huggingface.co/cahya/wav2vec2-base-turkish-artificial-cv) on the COMMON_VOICE - TR dataset.
  It achieves the following results on the evaluation set:
  
   
  |     | Dataset                       | WER     | CER      |
  |---|-------------------------------|---------|----------|
  | 1   | Common Voice 6.1              |  9.437  |  3.325   |
  | 2   | Common Voice 7.0              |  8.147  |  2.802   |
  | 3   | Common Voice 8.0              |  8.335  |  2.336   |
  | 4   | Speech Recognition Community  | 28.011  | 10.66    |
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  The following datasets were used for finetuning:
   - [Common Voice 7.0 TR](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0) 'train', 'validation' and 'other' split were used for training.
   - [Media Speech](https://www.openslr.org/108/)
   - [Magic Hub](https://magichub.com/)
  
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 7.5e-06
  - train_batch_size: 6
  - eval_batch_size: 2
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 24
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 2000
  - num_epochs: 5.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.1224        | 3.45  | 500  | 0.1641          | 0.1396 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.18.2
  - Tokenizers 0.10.3
  