--- license: mit base_model: roberta-base tags: - generated_from_trainer metrics: - f1 - accuracy model-index: - name: RewardModel_RobertaBase results: [] --- # RewardModel_RobertaBase This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5050 - F1: 0.7522 - Roc Auc: 0.7526 - Accuracy: 0.7509 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| | 0.6464 | 1.0 | 100 | 0.6186 | 0.6772 | 0.6772 | 0.6737 | | 0.5776 | 2.0 | 200 | 0.5439 | 0.7298 | 0.7298 | 0.7298 | | 0.4806 | 3.0 | 300 | 0.5050 | 0.7522 | 0.7526 | 0.7509 | | 0.3909 | 4.0 | 400 | 0.8594 | 0.6690 | 0.6684 | 0.6667 | | 0.331 | 5.0 | 500 | 0.7766 | 0.7206 | 0.7211 | 0.7193 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1