Modernbert Pii Ner

--- library_name: transformers license: apache-2.0 base_model: answerdotai/ModernBERT-base tags: - trackio - trackio:https://huggingface.co/spaces/jefftherover/huggingface-static-6bdbc7 - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: modernbert-pii-ner results: [] --- # modernbert-pii-ner This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1431 - Precision: 0.9096 - Recall: 0.9466 - F1: 0.9277 - Accuracy: 0.9683 ## 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: 5e-05 - train_batch_size: 16 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine_with_restarts - lr_scheduler_warmup_steps: 0.2 - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | 0.4505 | 0.4087 | 500 | 0.2343 | 0.6446 | 0.7708 | 0.7020 | 0.9337 | | 0.2362 | 0.8173 | 1000 | 0.1324 | 0.7922 | 0.8659 | 0.8274 | 0.9299 | | 0.1772 | 1.2256 | 1500 | 0.0934 | 0.8931 | 0.9199 | 0.9063 | 0.9640 | | 0.1567 | 1.6342 | 2000 | 0.0807 | 0.8926 | 0.9343 | 0.9130 | 0.9653 | | 0.1416 | 2.0425 | 2500 | 0.0772 | 0.8626 | 0.9288 | 0.8945 | 0.9570 | | 0.1197 | 2.4512 | 3000 | 0.0763 | 0.8855 | 0.9370 | 0.9105 | 0.9643 | | 0.1091 | 2.8598 | 3500 | 0.0731 | 0.9072 | 0.9473 | 0.9268 | 0.9688 | | 0.0868 | 3.2681 | 4000 | 0.0774 | 0.9155 | 0.9486 | 0.9317 | 0.9688 | | 0.0681 | 3.6767 | 4500 | 0.0880 | 0.9098 | 0.9483 | 0.9286 | 0.9684 | | 0.0263 | 4.0850 | 5000 | 0.1211 | 0.9102 | 0.9460 | 0.9278 | 0.9674 | | 0.0187 | 4.4937 | 5500 | 0.1431 | 0.9096 | 0.9466 | 0.9277 | 0.9683 | ### Framework versions - Transformers 5.7.0 - Pytorch 2.11.0+cu130 - Datasets 4.8.5 - Tokenizers 0.22.2