| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: FacebookAI/roberta-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: roberta-base-kennedy2020constructing |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # roberta-base-kennedy2020constructing |
| |
|
| | This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2110 |
| | - Accuracy: 0.9738 |
| | - Roc Auc: 0.9915 |
| | - Precision: 0.9680 |
| | - Recall: 0.9592 |
| | - F1: 0.9636 |
| |
|
| | ## 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: 96 |
| | - eval_batch_size: 128 |
| | - seed: 42 |
| | - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Roc Auc | Precision | Recall | F1 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|:---------:|:------:|:------:| |
| | | 0.2481 | 1.0 | 1144 | 0.2172 | 0.9001 | 0.9676 | 0.9266 | 0.7861 | 0.8506 | |
| | | 0.1822 | 2.0 | 2288 | 0.1604 | 0.9380 | 0.9836 | 0.9252 | 0.9017 | 0.9133 | |
| | | 0.1085 | 3.0 | 3432 | 0.1343 | 0.9575 | 0.9893 | 0.9627 | 0.9180 | 0.9398 | |
| | | 0.0674 | 4.0 | 4576 | 0.1225 | 0.9649 | 0.9918 | 0.9477 | 0.9558 | 0.9517 | |
| | | 0.0502 | 5.0 | 5720 | 0.1455 | 0.9688 | 0.9919 | 0.9561 | 0.9576 | 0.9569 | |
| | | 0.0365 | 6.0 | 6864 | 0.1370 | 0.9698 | 0.9921 | 0.9676 | 0.9481 | 0.9578 | |
| | | 0.0258 | 7.0 | 8008 | 0.1719 | 0.9706 | 0.9925 | 0.9615 | 0.9570 | 0.9592 | |
| | | 0.0184 | 8.0 | 9152 | 0.1737 | 0.9731 | 0.9922 | 0.9686 | 0.9567 | 0.9626 | |
| | | 0.0141 | 9.0 | 10296 | 0.2051 | 0.9734 | 0.9916 | 0.9673 | 0.9588 | 0.9630 | |
| | | 0.01 | 10.0 | 11440 | 0.2110 | 0.9738 | 0.9915 | 0.9680 | 0.9592 | 0.9636 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.49.0 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.3.2 |
| | - Tokenizers 0.21.0 |
| | |
