--- 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: 0.3567 - Accuracy: 0.8396 - F1-score: 0.7752 - Precision: 0.7713 - Recall: 0.7794 - Auc: 0.7794 ## 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: 64 - eval_batch_size: 64 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:| | 0.4074 | 1.0 | 39 | 0.3802 | 0.8347 | 0.7643 | 0.7649 | 0.7636 | 0.7636 | | 0.297 | 2.0 | 78 | 0.3567 | 0.8396 | 0.7752 | 0.7713 | 0.7794 | 0.7794 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Datasets 2.17.0 - Tokenizers 0.15.1