--- library_name: transformers language: - nl license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - procit009/nl_stt metrics: - wer model-index: - name: 'Whisper Small nl ' results: [] --- # Whisper Small nl This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the procit009/nl_stt dataset. It achieves the following results on the evaluation set: - Loss: 0.2637 - Wer: 14.1492 ## 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: 16 - eval_batch_size: 5 - 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: 200 - num_epochs: 6 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.2302 | 1.0 | 125 | 0.2444 | 14.2023 | | 0.1247 | 2.0 | 250 | 0.2396 | 14.4464 | | 0.036 | 3.0 | 375 | 0.2448 | 13.9582 | | 0.0117 | 4.0 | 500 | 0.2549 | 14.0113 | | 0.0049 | 5.0 | 625 | 0.2604 | 15.5928 | | 0.0031 | 6.0 | 750 | 0.2637 | 14.1492 | ### Framework versions - Transformers 4.47.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0