--- 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: 106.09137055837563 --- # 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: 3.0264 - Wer: 106.0914 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.3022 | 12.5 | 200 | 2.6624 | 109.5431 | | 0.0077 | 25.0 | 400 | 2.8312 | 105.1777 | | 0.0012 | 37.5 | 600 | 2.9571 | 110.4569 | | 0.0008 | 50.0 | 800 | 3.0120 | 107.6142 | | 0.0007 | 62.5 | 1000 | 3.0264 | 106.0914 | ### Framework versions - Transformers 4.46.0.dev0 - Pytorch 2.4.1+cu121 - Datasets 3.0.1 - Tokenizers 0.20.1