--- license: apache-2.0 base_model: openai/whisper-large-v3 tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-large-v3-turbo-ft-cv-cy-train-all-plus-other-with-excluded results: [] --- # whisper-large-v3-turbo-ft-cv-cy-train-all-plus-other-with-excluded 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 train_all+other_with_excluded main dataset. It achieves the following results on the evaluation set: - Loss: 0.3181 - Wer: 0.1683 ## 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 | |:-------------:|:------:|:----:|:---------------:|:------:| | 0.1599 | 1.4144 | 1000 | 0.2516 | 0.2035 | | 0.0651 | 2.8289 | 2000 | 0.2339 | 0.1831 | | 0.0119 | 4.2433 | 3000 | 0.2720 | 0.1751 | | 0.005 | 5.6577 | 4000 | 0.2928 | 0.1692 | | 0.0009 | 7.0721 | 5000 | 0.3181 | 0.1683 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1