--- license: mit tags: - generated_from_trainer datasets: - conll2003 model_index: - name: roberta-base-ner results: - task: name: Token Classification type: token-classification dataset: name: conll2003 type: conll2003 args: conll2003 --- # roberta-base-ner This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the conll2003 dataset. It achieves the following results on the evaluation set: - eval_loss: 0.0814 - eval_precision: 0.9101 - eval_recall: 0.9336 - eval_f1: 0.9217 - eval_accuracy: 0.9799 - eval_runtime: 10.2964 - eval_samples_per_second: 315.646 - eval_steps_per_second: 39.529 - epoch: 1.14 - step: 500 ## 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: 32 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4.0 ### Framework versions - Transformers 4.8.2 - Pytorch 1.8.1+cu111 - Datasets 1.8.0 - Tokenizers 0.10.3