--- base_model: openai/whisper-large-v3 datasets: - BembaSpeech license: apache-2.0 metrics: - wer tags: - generated_from_trainer model-index: - name: whisper-large-v3-bem results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: BembaSpeech bem type: BembaSpeech args: bem metrics: - type: wer value: 0.375750300120048 name: Wer - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: bembaspeech type: bembaspeech config: bem split: test metrics: - type: wer value: 37.96 name: WER - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: BembaSpeech type: BembaSpeech config: bem split: test metrics: - type: wer value: 37.96 name: WER - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: BembaSpeech type: BembaSpeech config: en split: test metrics: - type: wer value: 41.89 name: WER --- # whisper-large-v3-bem This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the BembaSpeech bem dataset. It achieves the following results on the evaluation set: - Loss: 0.3448 - Wer: 0.3758 ## 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: 1.75e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 6 - total_train_batch_size: 24 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 2.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:------:| | 0.4685 | 1.0084 | 500 | 0.3448 | 0.3758 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1