metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: RewardModel_RobertaBase
results: []
RewardModel_RobertaBase
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1713
- F1: 0.9670
- Roc Auc: 0.9670
- Accuracy: 0.9670
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 63 | 0.1713 | 0.9670 | 0.9670 | 0.9670 |
| 0.1703 | 2.0 | 126 | 0.1866 | 0.9670 | 0.9670 | 0.9670 |
| 0.1703 | 3.0 | 189 | 0.1876 | 0.9670 | 0.9670 | 0.9670 |
| 0.0284 | 4.0 | 252 | 0.1917 | 0.9670 | 0.9670 | 0.9670 |
| 0.0283 | 5.0 | 315 | 0.1924 | 0.9670 | 0.9670 | 0.9670 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0