--- license: apache-2.0 base_model: distilbert/distilroberta-base tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: distilroberta-512-fbeta1.6 results: [] --- # distilroberta-512-fbeta1.6 This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0736 - Accuracy: 0.9814 - F1: 0.9752 - Fbeta 1.6: 0.9766 - False positive rate: 0.0169 - False negative rate: 0.0216 - Precision: 0.9721 - Recall: 0.9784 ## 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: 1e-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 - lr_scheduler_warmup_steps: 600 - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Fbeta 1.6 | False positive rate | False negative rate | Precision | Recall | |:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|:---------:|:-------------------:|:-------------------:|:---------:|:------:| | 0.3325 | 0.0998 | 586 | 0.1839 | 0.9479 | 0.9280 | 0.9132 | 0.0202 | 0.1052 | 0.9638 | 0.8948 | | 0.1161 | 0.1997 | 1172 | 0.0958 | 0.9682 | 0.9576 | 0.9577 | 0.0256 | 0.0422 | 0.9574 | 0.9578 | | 0.1006 | 0.2995 | 1758 | 0.0959 | 0.9716 | 0.9616 | 0.9554 | 0.0140 | 0.0524 | 0.9761 | 0.9476 | | 0.0984 | 0.3994 | 2344 | 0.0776 | 0.9717 | 0.9628 | 0.9674 | 0.0293 | 0.0265 | 0.9523 | 0.9735 | | 0.0897 | 0.4992 | 2930 | 0.0994 | 0.9676 | 0.9580 | 0.9696 | 0.0428 | 0.0151 | 0.9326 | 0.9849 | | 0.0856 | 0.5991 | 3516 | 0.0889 | 0.9751 | 0.9670 | 0.9684 | 0.0219 | 0.0299 | 0.9638 | 0.9701 | | 0.0779 | 0.6989 | 4102 | 0.0842 | 0.9762 | 0.9681 | 0.9652 | 0.0149 | 0.0385 | 0.9749 | 0.9615 | | 0.0821 | 0.7988 | 4688 | 0.0702 | 0.9768 | 0.9693 | 0.9723 | 0.0228 | 0.0239 | 0.9626 | 0.9761 | | 0.073 | 0.8986 | 5274 | 0.0773 | 0.9776 | 0.9703 | 0.9727 | 0.0213 | 0.0243 | 0.9650 | 0.9757 | | 0.0775 | 0.9985 | 5860 | 0.0709 | 0.9774 | 0.9701 | 0.9721 | 0.0210 | 0.0252 | 0.9653 | 0.9748 | | 0.0627 | 1.0983 | 6446 | 0.0646 | 0.9789 | 0.9720 | 0.9737 | 0.0193 | 0.0240 | 0.9681 | 0.9760 | | 0.0648 | 1.1982 | 7032 | 0.0729 | 0.9787 | 0.9716 | 0.9708 | 0.0158 | 0.0303 | 0.9735 | 0.9697 | | 0.0592 | 1.2980 | 7618 | 0.0733 | 0.9802 | 0.9735 | 0.9725 | 0.0144 | 0.0289 | 0.9760 | 0.9711 | | 0.0585 | 1.3979 | 8204 | 0.0764 | 0.9790 | 0.9720 | 0.9723 | 0.0173 | 0.0273 | 0.9713 | 0.9727 | | 0.0579 | 1.4977 | 8790 | 0.0691 | 0.9782 | 0.9712 | 0.9739 | 0.0214 | 0.0225 | 0.9649 | 0.9775 | | 0.0584 | 1.5975 | 9376 | 0.0739 | 0.9797 | 0.9732 | 0.9755 | 0.0195 | 0.0215 | 0.9679 | 0.9785 | | 0.0564 | 1.6974 | 9962 | 0.0749 | 0.9774 | 0.9703 | 0.9757 | 0.0257 | 0.0173 | 0.9583 | 0.9827 | | 0.0582 | 1.7972 | 10548 | 0.0721 | 0.9804 | 0.9739 | 0.9742 | 0.0162 | 0.0253 | 0.9730 | 0.9747 | | 0.0576 | 1.8971 | 11134 | 0.0746 | 0.9799 | 0.9732 | 0.9734 | 0.0163 | 0.0264 | 0.9729 | 0.9736 | | 0.0546 | 1.9969 | 11720 | 0.0758 | 0.9804 | 0.9739 | 0.9736 | 0.0152 | 0.0269 | 0.9747 | 0.9731 | | 0.0431 | 2.0968 | 12306 | 0.0755 | 0.9805 | 0.9741 | 0.9762 | 0.0186 | 0.0211 | 0.9694 | 0.9789 | | 0.0464 | 2.1966 | 12892 | 0.0785 | 0.9802 | 0.9737 | 0.9735 | 0.0156 | 0.0266 | 0.9740 | 0.9734 | | 0.0443 | 2.2965 | 13478 | 0.0763 | 0.9811 | 0.9748 | 0.9734 | 0.0132 | 0.0283 | 0.9779 | 0.9717 | | 0.0426 | 2.3963 | 14064 | 0.0753 | 0.9812 | 0.9750 | 0.9760 | 0.0165 | 0.0227 | 0.9727 | 0.9773 | | 0.0413 | 2.4962 | 14650 | 0.0750 | 0.9811 | 0.9748 | 0.9760 | 0.0168 | 0.0225 | 0.9722 | 0.9775 | | 0.0442 | 2.5960 | 15236 | 0.0756 | 0.9813 | 0.9752 | 0.9766 | 0.0169 | 0.0216 | 0.9720 | 0.9784 | | 0.043 | 2.6959 | 15822 | 0.0810 | 0.9814 | 0.9750 | 0.9729 | 0.0119 | 0.0299 | 0.98 | 0.9701 | | 0.0433 | 2.7957 | 16408 | 0.0783 | 0.9814 | 0.9751 | 0.9733 | 0.0125 | 0.0289 | 0.9790 | 0.9711 | | 0.0398 | 2.8956 | 16994 | 0.0736 | 0.9814 | 0.9752 | 0.9766 | 0.0169 | 0.0216 | 0.9721 | 0.9784 | | 0.0431 | 2.9954 | 17580 | 0.0757 | 0.9816 | 0.9754 | 0.9757 | 0.0151 | 0.0240 | 0.9749 | 0.9760 | ### Framework versions - Transformers 4.40.1 - Pytorch 2.3.0+cu121 - Datasets 2.19.0 - Tokenizers 0.19.1