--- license: apache-2.0 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: roberta-base-biomedical-clinical-es-finetuned-ner-Concat_CRAFT_es results: [] --- # roberta-base-biomedical-clinical-es-finetuned-ner-Concat_CRAFT_es This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-biomedical-clinical-es](https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-clinical-es) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1874 - Precision: 0.8559 - Recall: 0.8425 - F1: 0.8492 - Accuracy: 0.9696 ## 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: 3e-05 - train_batch_size: 8 - 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 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| | 0.072 | 1.0 | 2719 | 0.1500 | 0.8138 | 0.8224 | 0.8181 | 0.9644 | | 0.0305 | 2.0 | 5438 | 0.1555 | 0.8417 | 0.8253 | 0.8334 | 0.9674 | | 0.014 | 3.0 | 8157 | 0.1743 | 0.8429 | 0.8412 | 0.8421 | 0.9685 | | 0.0076 | 4.0 | 10876 | 0.1874 | 0.8559 | 0.8425 | 0.8492 | 0.9696 | ### Framework versions - Transformers 4.17.0 - Pytorch 1.10.0+cu111 - Datasets 1.18.4 - Tokenizers 0.11.6