--- library_name: transformers license: mit base_model: roberta-large tags: - generated_from_trainer model-index: - name: machiavellianism_continuous results: [] --- # machiavellianism_continuous This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0575 - Rmse: 0.2398 - Mae: 0.1972 - Corr: 0.4360 ## 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 | 267 | 0.0589 | 0.2426 | 0.1975 | 0.4210 | | 0.0805 | 2.0 | 534 | 0.0575 | 0.2398 | 0.1972 | 0.4360 | ### Framework versions - Transformers 4.44.1 - Pytorch 1.11.0 - Datasets 2.12.0 - Tokenizers 0.19.1