--- license: apache-2.0 base_model: BSC-TeMU/roberta-base-bne tags: - generated_from_trainer metrics: - accuracy - precision - recall model-index: - name: roberta-base-bne-finetuned-detests-wandb24 results: [] --- # roberta-base-bne-finetuned-detests-wandb24 This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3730 - Accuracy: 0.8592 - F1-score: 0.7922 - Precision: 0.8046 - Recall: 0.7820 - Auc: 0.7820 ## 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: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall | Auc | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:| | 0.344 | 1.0 | 77 | 0.3268 | 0.8642 | 0.7814 | 0.8347 | 0.7522 | 0.7522 | | 0.1996 | 2.0 | 154 | 0.3730 | 0.8592 | 0.7922 | 0.8046 | 0.7820 | 0.7820 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Datasets 2.17.0 - Tokenizers 0.15.1