--- license: apache-2.0 base_model: bert-base-uncased tags: - generated_from_trainer datasets: - conll2003 metrics: - f1 model-index: - name: bert-base-uncased-for-ner results: - task: name: Token Classification type: token-classification dataset: name: conll2003 type: conll2003 config: conll2003 split: validation args: conll2003 metrics: - name: F1 type: f1 value: 0.95092693565976 --- # bert-base-uncased-for-ner This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the conll2003 dataset. It achieves the following results on the evaluation set: - Loss: 0.0425 - F1: 0.9509 ## 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: 24 - eval_batch_size: 24 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.1058 | 1.0 | 586 | 0.0446 | 0.9343 | | 0.0282 | 2.0 | 1172 | 0.0405 | 0.9454 | | 0.0125 | 3.0 | 1758 | 0.0425 | 0.9509 | ### Framework versions - Transformers 4.43.3 - Pytorch 2.4.0 - Datasets 2.20.0 - Tokenizers 0.19.1