--- 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 Small 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: 17.210750075918614 --- # Whisper Small Turkish This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 tr dataset. It achieves the following results on the evaluation set: - Loss: 0.2611 - Wer: 17.2108 ## Model description The Whisper small model is fine-tuned on CommonVoice Turkish train+validation partitions. The model was fine-tuend for 1000 steps. Without fine-tuning the WER on test data was 23.7 (using whsiper-small and the CommonVoice 9 test data). ## 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: 64 - eval_batch_size: 32 - 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: 1000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0693 | 3.05 | 1000 | 0.2611 | 17.2108 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2