readme: ---
  language:
  - tr
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: ''
    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. -->
  
  # 
  
  This model is a fine-tuned version of [cahya/wav2vec2-base-turkish-artificial](https://huggingface.co/cahya/wav2vec2-base-turkish-artificial) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - TR dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2893
  - Wer: 0.2713
  
  ## 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: 128
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 512
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 100
  - num_epochs: 100.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.8647        | 14.28 | 200  | 0.2758          | 0.2568 |
  | 1.3376        | 28.56 | 400  | 0.2754          | 0.2722 |
  | 1.1975        | 42.84 | 600  | 0.2929          | 0.2901 |
  | 1.1024        | 57.14 | 800  | 0.2904          | 0.2928 |
  | 1.0257        | 71.42 | 1000 | 0.2915          | 0.2823 |
  | 0.9628        | 85.7  | 1200 | 0.2936          | 0.2749 |
  | 0.9109        | 99.98 | 1400 | 0.2893          | 0.2713 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  