--- language: - cr license: apache-2.0 base_model: openai/whisper-large-v3 tags: - generated_from_trainer datasets: - audiofolder metrics: - wer model-index: - name: whisper-large-v3-croatian-v3 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: audiofolder type: audiofolder config: default split: train args: 'config: cr, split: test' metrics: - name: Wer type: wer value: 74.31180859274504 --- # whisper-large-v3-croatian-v3 This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the audiofolder dataset. It achieves the following results on the evaluation set: - Loss: 2.8726 - Wer: 74.3118 ## 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: 1.25e-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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0539 | 13.89 | 1000 | 2.3264 | 87.0594 | | 0.0116 | 27.78 | 2000 | 2.5778 | 91.6517 | | 0.0072 | 41.67 | 3000 | 2.8216 | 76.4729 | | 0.0074 | 55.56 | 4000 | 2.8726 | 74.3118 | ### Framework versions - Transformers 4.36.1 - Pytorch 2.1.1+cu121 - Datasets 2.15.0 - Tokenizers 0.15.0