--- license: apache-2.0 base_model: openai/whisper-large-v3 tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_16_0 metrics: - wer model-index: - name: whisper-large-v3-pt-cv16-cuda results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_16_0 pt type: mozilla-foundation/common_voice_16_0 split: None args: pt metrics: - name: Wer type: wer value: 0.9998545572074984 --- # whisper-large-v3-pt-cv16-cuda This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the mozilla-foundation/common_voice_16_0 pt dataset. It achieves the following results on the evaluation set: - Loss: 0.1325 - Wer: 0.9999 ## 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-06 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 2000 - training_steps: 5000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.199 | 0.26 | 1000 | 0.1563 | 0.1124 | | 0.1654 | 0.52 | 2000 | 0.1500 | 0.1052 | | 0.1794 | 0.77 | 3000 | 0.1379 | 0.0997 | | 0.0821 | 1.03 | 4000 | 0.1321 | 1.0007 | | 0.1292 | 1.29 | 5000 | 0.1325 | 0.9999 | ### Framework versions - Transformers 4.37.0.dev0 - Pytorch 2.2.0.dev20231212 - Datasets 2.15.1.dev0 - Tokenizers 0.15.0