| license: mit | |
| base_model: roberta-base | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: Cautiousness_continuous | |
| 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. --> | |
| # 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 | |