metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: HarmCare_continuous
results: []
HarmCare_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: 0.0254
- Rmse: 0.1595
- Mae: 0.1246
- Corr: 0.2532
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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Rmse | Mae | Corr |
---|---|---|---|---|---|---|
No log | 1.0 | 253 | 0.0284 | 0.1684 | 0.1301 | 0.2060 |
0.0376 | 2.0 | 506 | 0.0267 | 0.1635 | 0.1326 | 0.2328 |
0.0376 | 3.0 | 759 | 0.0254 | 0.1595 | 0.1246 | 0.2532 |
Framework versions
- Transformers 4.44.1
- Pytorch 1.11.0
- Datasets 2.12.0
- Tokenizers 0.19.1