metadata
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 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