charisgao/finetuned-roberta-bias-classification

model

This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.6344
• Precision: 0.8128
• Recall: 0.9363
• F1: 0.8702
• Accuracy: 0.8161

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use 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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.578	0.8547	100	0.5079	0.8108	0.8824	0.8451	0.7871
0.4531	1.7094	200	0.4576	0.8462	0.8627	0.8544	0.8065
0.3272	2.5641	300	0.6344	0.8128	0.9363	0.8702	0.8161

Framework versions

• Transformers 4.46.2
• Pytorch 2.5.1+cu121
• Tokenizers 0.20.3