--- library_name: transformers language: - pmx license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - iitd-duk/paula metrics: - wer model-index: - name: Whisper-Small-paula results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Paula type: iitd-duk/paula metrics: - name: Wer type: wer value: 101.20160213618156 --- # Whisper-Small-paula This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the Paula dataset. It achieves the following results on the evaluation set: - Loss: 3.2127 - Wer: 101.2016 ## 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: 12 - eval_batch_size: 8 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - training_steps: 1000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.3498 | 10.5263 | 200 | 2.7008 | 103.7383 | | 0.0082 | 21.0526 | 400 | 2.9834 | 97.4633 | | 0.0019 | 31.5789 | 600 | 3.1297 | 103.3378 | | 0.0009 | 42.1053 | 800 | 3.1949 | 101.7356 | | 0.0007 | 52.6316 | 1000 | 3.2127 | 101.2016 | ### Framework versions - Transformers 4.46.0.dev0 - Pytorch 2.4.1+cu121 - Datasets 3.0.1 - Tokenizers 0.20.1