--- language: - tr license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Medium Turkish results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_11_0 tr type: mozilla-foundation/common_voice_11_0 config: tr split: test args: tr metrics: - name: Wer type: wer value: 11.068934102641968 --- # Whisper Medium Turkish This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 tr dataset. It achieves the following results on the evaluation set: - Loss: 0.2780 - Wer: 11.0689 ## 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: 32 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 5000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0742 | 1.07 | 1000 | 0.2104 | 12.3975 | | 0.0345 | 3.02 | 2000 | 0.2182 | 11.6573 | | 0.0103 | 4.09 | 3000 | 0.2489 | 11.7921 | | 0.0018 | 6.04 | 4000 | 0.2657 | 11.0746 | | 0.0005 | 7.11 | 5000 | 0.2780 | 11.0689 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2