--- 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: 102.84463894967178 --- # 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: 3.1674 - Wer: 102.8446 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.3851 | 10.0 | 200 | 2.6828 | 101.7505 | | 0.0097 | 20.0 | 400 | 2.9628 | 101.5317 | | 0.002 | 30.0 | 600 | 3.1073 | 100.2188 | | 0.001 | 40.0 | 800 | 3.1528 | 101.9694 | | 0.0008 | 50.0 | 1000 | 3.1674 | 102.8446 | ### Framework versions - Transformers 4.46.0.dev0 - Pytorch 2.4.1+cu121 - Datasets 3.0.1 - Tokenizers 0.20.1