--- license: apache-2.0 base_model: openai/whisper-large-v3 tags: - generated_from_trainer datasets: - honzapucalek/impaired_v3_independent_severe metrics: - wer model-index: - name: impaired-v3-independent-severe results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: honzapucalek/impaired_v3_independent_severe cs type: honzapucalek/impaired_v3_independent_severe config: cs split: test args: cs metrics: - name: Wer type: wer value: 0.42105263157894735 --- # impaired-v3-independent-severe This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the honzapucalek/impaired_v3_independent_severe cs dataset. It achieves the following results on the evaluation set: - Loss: 1.5988 - Wer: 0.4211 ## 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: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 5000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:------:| | 0.0001 | 95.24 | 1000 | 1.3804 | 0.4160 | | 0.0 | 190.48 | 2000 | 1.4914 | 0.4160 | | 0.0 | 285.71 | 3000 | 1.5487 | 0.4221 | | 0.0 | 380.95 | 4000 | 1.5853 | 0.4251 | | 0.0 | 476.19 | 5000 | 1.5988 | 0.4211 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.2+cu121 - Datasets 2.16.1 - Tokenizers 0.15.1