--- language: - tr license: apache-2.0 base_model: openai/whisper-small tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_16_1 metrics: - wer model-index: - name: Whisper Small Tr V2 - Atakan Ince results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 16.1 type: mozilla-foundation/common_voice_16_1 config: tr split: None args: 'config: tr, split: test' metrics: - name: Wer type: wer value: 20.395363464821635 --- # Whisper Small Tr V2 - Atakan Ince This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set: - Loss: 0.2221 - Wer: 20.3954 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.199 | 0.37 | 1000 | 0.2704 | 24.3238 | | 0.1476 | 0.73 | 2000 | 0.2443 | 22.2284 | | 0.0768 | 1.1 | 3000 | 0.2280 | 20.7674 | | 0.0813 | 1.46 | 4000 | 0.2221 | 20.3954 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.1.0+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2