--- library_name: transformers license: apache-2.0 base_model: openai/whisper-large-v3 tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-large-v3-ft-btb-ca-cy results: [] --- # whisper-large-v3-ft-btb-ca-cy This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the DewiBrynJones/banc-trawsgrifiadau-bangor-clean train main, cymen-arfor/25awr train+dev main dataset. It achieves the following results on the evaluation set: - Loss: 0.3810 - Wer: 0.2750 ## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - 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 | |:-------------:|:------:|:----:|:---------------:|:------:| | 0.5152 | 0.5411 | 1000 | 0.4954 | 0.3535 | | 0.3339 | 1.0823 | 2000 | 0.4205 | 0.3198 | | 0.3189 | 1.6234 | 3000 | 0.3911 | 0.2913 | | 0.2051 | 2.1645 | 4000 | 0.3863 | 0.2790 | | 0.202 | 2.7056 | 5000 | 0.3810 | 0.2750 | ### Framework versions - Transformers 4.46.2 - Pytorch 2.5.1+cu124 - Datasets 3.1.0 - Tokenizers 0.20.3