--- license: cc-by-nc-3.0 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: roberta-large-NER results: [] --- # roberta-large-NER This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1053 - Precision: 0.6030 - Recall: 0.5688 - F1: 0.5854 - Accuracy: 0.9628 ## 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: 2e-05 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | 0.1188 | 1.0 | 2714 | 0.1053 | 0.6030 | 0.5688 | 0.5854 | 0.9628 | ### Framework versions - Transformers 4.34.1 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1