--- license: apache-2.0 tags: - generated_from_trainer metrics: - wer model-index: - name: openai/whisper-small results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: rishabhjain16/infer_myst type: rishabhjain16/infer_myst config: en split: test metrics: - type: wer value: 13.29 name: WER - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: rishabhjain16/infer_cmu type: rishabhjain16/infer_cmu config: en split: test metrics: - type: wer value: 12.26 name: WER - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: rishabhjain16/libritts_dev_clean type: rishabhjain16/libritts_dev_clean config: en split: test metrics: - type: wer value: 6.5 name: WER --- # openai/whisper-small This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5154 - Wer: 13.4267 ## 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: 3000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.167 | 2.01 | 500 | 0.3235 | 13.2309 | | 0.1796 | 4.03 | 1000 | 0.3410 | 12.8549 | | 0.0274 | 6.04 | 1500 | 0.4035 | 13.0246 | | 0.0305 | 8.06 | 2000 | 0.4462 | 13.4476 | | 0.0041 | 10.07 | 2500 | 0.5034 | 13.3144 | | 0.0046 | 13.01 | 3000 | 0.5154 | 13.4267 | ### Framework versions - Transformers 4.27.0.dev0 - Pytorch 1.13.1+cu117 - Datasets 2.9.1.dev0 - Tokenizers 0.13.2