--- license: mit base_model: roberta-base tags: - generated_from_trainer model-index: - name: Cautiousness_continuous results: [] --- # Cautiousness_continuous 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: 0.0643 - Rmse: 0.2535 - Mae: 0.2055 - Corr: 0.3439 ## 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: 32 - eval_batch_size: 32 - 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 | Rmse | Mae | Corr | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:| | No log | 1.0 | 268 | 0.0622 | 0.2494 | 0.2047 | 0.3288 | | 0.0729 | 2.0 | 536 | 0.0643 | 0.2535 | 0.2055 | 0.3439 | ### Framework versions - Transformers 4.43.3 - Pytorch 2.4.0 - Datasets 2.20.0 - Tokenizers 0.19.1