--- language: - sr license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - espnet/yodas metrics: - wer model-index: - name: Whisper Small Sr Yodas results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Yodas type: espnet/yodas config: sr split: test args: sr metrics: - name: Wer type: wer value: 0.24497708847373986 --- # Whisper Small Sr Yodas This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Yodas dataset. It achieves the following results on the evaluation set: - Loss: 0.2688 - Wer Ortho: 0.3334 - Wer: 0.2450 ## 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: 50 - training_steps: 4000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| | 1.0469 | 0.24 | 500 | 0.4020 | 0.5071 | 0.4270 | | 0.9924 | 0.49 | 1000 | 0.3401 | 0.4082 | 0.3183 | | 0.865 | 0.73 | 1500 | 0.3047 | 0.3644 | 0.2776 | | 0.8443 | 0.98 | 2000 | 0.2893 | 0.3623 | 0.2735 | | 0.7377 | 1.22 | 2500 | 0.2817 | 0.3472 | 0.2591 | | 0.6851 | 1.46 | 3000 | 0.2728 | 0.3348 | 0.2466 | | 0.7286 | 1.71 | 3500 | 0.2702 | 0.3325 | 0.2444 | | 0.7215 | 1.95 | 4000 | 0.2688 | 0.3334 | 0.2450 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.0.1+cu117 - Datasets 2.18.0 - Tokenizers 0.15.1