--- license: apache-2.0 base_model: openai/whisper-large-v3 tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-large-v3-ft-cv-cy-en results: [] --- # whisper-large-v3-ft-cv-cy-en This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the DewiBrynJones/commonvoice_18_0_cy_en train main dataset. It achieves the following results on the evaluation set: - Loss: 0.3036 - Wer: 0.1826 ## 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: 16 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - 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 | |:-------------:|:------:|:----:|:---------------:|:------:| | 0.294 | 0.7075 | 1000 | 0.3054 | 0.2114 | | 0.1572 | 1.4149 | 2000 | 0.2768 | 0.1898 | | 0.0714 | 2.1224 | 3000 | 0.2789 | 0.1807 | | 0.0772 | 2.8299 | 4000 | 0.2759 | 0.1810 | | 0.0337 | 3.5373 | 5000 | 0.3036 | 0.1826 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1