--- license: apache-2.0 tags: - generated_from_trainer datasets: - common_voice_11_0 metrics: - wer model-index: - name: openai/whisper-small results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: common_voice_11_0 type: common_voice_11_0 config: ja split: test args: ja metrics: - name: Wer type: wer value: 13.474662162162163 --- # openai/whisper-small This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_11_0 dataset. It achieves the following results on the evaluation set: - Loss: 0.4319 - Wer: 13.4747 - Cer: 8.6213 ## 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: 64 - eval_batch_size: 32 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:| | 0.0167 | 7.0 | 1000 | 0.3066 | 13.6740 | 8.5733 | | 0.0021 | 14.01 | 2000 | 0.3579 | 13.8733 | 8.7816 | | 0.0006 | 21.01 | 3000 | 0.4025 | 13.5794 | 8.6173 | | 0.0004 | 28.01 | 4000 | 0.4232 | 13.4679 | 8.6022 | | 0.0004 | 35.01 | 5000 | 0.4319 | 13.4747 | 8.6213 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.12.1+cu113 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2