--- library_name: transformers license: apache-2.0 base_model: answerdotai/ModernBERT-base tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: RewardModel_ModernBERT-base results: [] --- # RewardModel_ModernBERT-base This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1843 - Accuracy: 1.0 - F1: 1.0 - Roc Auc: 1.0 ## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Roc Auc | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:-------:| | No log | 1.0 | 10 | 0.1843 | 1.0 | 1.0 | 1.0 | | No log | 2.0 | 20 | 0.0083 | 1.0 | 1.0 | 1.0 | | No log | 3.0 | 30 | 0.0010 | 1.0 | 1.0 | 1.0 | | No log | 4.0 | 40 | 0.0001 | 1.0 | 1.0 | 1.0 | | No log | 5.0 | 50 | 0.0001 | 1.0 | 1.0 | 1.0 | ### Framework versions - Transformers 4.54.0 - Pytorch 2.6.0+cu124 - Datasets 4.0.0 - Tokenizers 0.21.2