--- language: - zh license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer base_model: openai/whisper-medium model-index: - name: Whisper medium nan-tw only char results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: mozilla-foundation/common_voice_11_0 nan-tw type: mozilla-foundation/common_voice_11_0 config: nan-tw split: test args: nan-tw metrics: - type: wer value: 45.2824427480916 name: Wer --- # Whisper medium nan-tw only char This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 nan-tw dataset. It achieves the following results on the evaluation set: - Loss: 0.9944 - Wer: 45.2824 - Cer: 45.3667 ## 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: 2 - eval_batch_size: 2 - seed: 42 - 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 | Cer | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| | 0.5832 | 1.04 | 1000 | 1.0634 | 56.3053 | 56.4745 | | 0.1467 | 2.08 | 2000 | 1.0407 | 50.9618 | 51.0112 | | 0.016 | 3.13 | 3000 | 1.0226 | 46.4427 | 46.5137 | | 0.0001 | 5.01 | 4000 | 0.9974 | 45.4656 | 45.6082 | | 0.0001 | 6.05 | 5000 | 0.9944 | 45.2824 | 45.3667 | ### Framework versions - Transformers 4.27.0.dev0 - Pytorch 1.13.1+cu117 - Datasets 2.8.0 - Tokenizers 0.13.2