readme: ---
  language:
  - tr
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: base Turkish Whisper (bTW)
    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. -->
  
  # base Turkish Whisper (bTW)
  
  This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Ermetal Meetings dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8800
  - Wer: 0.8060
  - Cer: 0.7585
  
  ## 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: 1e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 1000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
  | 1.8904        | 1.32  | 100  | 1.5873          | 0.8893 | 0.5437 |
  | 0.8039        | 2.63  | 200  | 0.9239          | 0.9076 | 0.5721 |
  | 0.5988        | 3.95  | 300  | 0.7970          | 0.7850 | 0.4821 |
  | 0.384         | 5.26  | 400  | 0.7586          | 0.7164 | 0.5206 |
  | 0.2643        | 6.58  | 500  | 0.7578          | 0.9130 | 0.6843 |
  | 0.2026        | 7.89  | 600  | 0.7627          | 0.9147 | 0.7228 |
  | 0.1091        | 9.21  | 700  | 0.8043          | 0.8363 | 0.8283 |
  | 0.0623        | 10.53 | 800  | 0.8342          | 0.7615 | 0.7619 |
  | 0.0436        | 11.84 | 900  | 0.8577          | 0.7079 | 0.6824 |
  | 0.0348        | 13.16 | 1000 | 0.8800          | 0.8060 | 0.7585 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.12.0+cu102
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  