--- language: - ku license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Small Kur - Rizgan Gerdenzeri results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 17.0 type: mozilla-foundation/common_voice_11_0 config: kmr split: None args: 'config: kmr, split: test' metrics: - name: Wer type: wer value: 35.26864147088866 --- # Whisper Small Kur - Rizgan Gerdenzeri This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.5986 - Wer: 35.2686 ## 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: 16 - eval_batch_size: 8 - 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: 4000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.3355 | 1.7699 | 1000 | 0.4746 | 40.3146 | | 0.0921 | 3.5398 | 2000 | 0.4746 | 36.7845 | | 0.0142 | 5.3097 | 3000 | 0.5598 | 36.6251 | | 0.004 | 7.0796 | 4000 | 0.5986 | 35.2686 | ### Framework versions - Transformers 4.43.3 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1