RewardModel_RobertaBase_GPT_Data

This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2827
• F1: 0.9076
• Roc Auc: 0.9420
• Accuracy: 0.8393

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
No log	1.0	16	0.6224	0.0	0.5	0.0
No log	2.0	32	0.5112	0.4658	0.6518	0.3036
No log	3.0	48	0.3407	0.8235	0.8571	0.75
No log	4.0	64	0.3243	0.85	0.8973	0.7679
No log	5.0	80	0.2827	0.9076	0.9420	0.8393

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1