--- license: apache-2.0 base_model: openai/whisper-base tags: - generated_from_trainer datasets: - common_voice_16_0 metrics: - wer model-index: - name: breeze-dsw-base-ml results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: common_voice_16_0 type: common_voice_16_0 config: ml split: test args: ml metrics: - name: Wer type: wer value: 44.21686746987952 --- # breeze-dsw-base-ml This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the common_voice_16_0 dataset. It achieves the following results on the evaluation set: - Loss: 0.7354 - Wer: 44.2169 ## 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: 32 - eval_batch_size: 16 - seed: 42 - distributed_type: multi-GPU - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 2000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.3151 | 4.02 | 200 | 0.4517 | 54.5134 | | 0.0703 | 9.02 | 400 | 0.4561 | 46.7285 | | 0.0144 | 14.02 | 600 | 0.5625 | 43.7627 | | 0.006 | 19.02 | 800 | 0.6260 | 42.7247 | | 0.0024 | 24.02 | 1000 | 0.6938 | 43.0306 | | 0.0012 | 29.02 | 1200 | 0.7354 | 44.2169 | ### Framework versions - Transformers 4.37.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.16.2.dev0 - Tokenizers 0.15.0