metadata
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: 0.5050
- F1: 0.7522
- Roc Auc: 0.7526
- Accuracy: 0.7509
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.6464 | 1.0 | 100 | 0.6186 | 0.6772 | 0.6772 | 0.6737 |
| 0.5776 | 2.0 | 200 | 0.5439 | 0.7298 | 0.7298 | 0.7298 |
| 0.4806 | 3.0 | 300 | 0.5050 | 0.7522 | 0.7526 | 0.7509 |
| 0.3909 | 4.0 | 400 | 0.8594 | 0.6690 | 0.6684 | 0.6667 |
| 0.331 | 5.0 | 500 | 0.7766 | 0.7206 | 0.7211 | 0.7193 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1