--- license: apache-2.0 base_model: openai/whisper-large-v3 tags: - generated_from_trainer datasets: - DewiBrynJones/commonvoice_18_0_cy metrics: - wer model-index: - name: whisper-large-v3-ft-cv-cy-train-all results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: DewiBrynJones/commonvoice_18_0_cy default type: DewiBrynJones/commonvoice_18_0_cy args: default metrics: - name: Wer type: wer value: 0.18173684838363355 --- # whisper-large-v3-ft-cv-cy-train-all 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 default dataset. It achieves the following results on the evaluation set: - Loss: 0.3638 - Wer: 0.1817 ## 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 | |:-------------:|:------:|:----:|:---------------:|:------:| | 0.1429 | 1.9455 | 1000 | 0.2754 | 0.2208 | | 0.0232 | 3.8911 | 2000 | 0.2916 | 0.1991 | | 0.0046 | 5.8366 | 3000 | 0.3219 | 0.1878 | | 0.0009 | 7.7821 | 4000 | 0.3454 | 0.1832 | | 0.0004 | 9.7276 | 5000 | 0.3638 | 0.1817 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1