BERT-political_bias-finetune

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

• Loss: 0.0945
• Accuracy: 0.9890
• Precision: 0.9962
• Recall: 0.9875
• F1: 0.9918

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: 5e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 0
• 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	Accuracy	Precision	Recall	F1
0.2651	0.1834	500	0.5210	0.8885	0.9981	0.8363	0.9101
0.1807	0.3668	1000	0.1013	0.9846	0.9913	0.9859	0.9885
0.0872	0.5503	1500	0.0693	0.9879	0.9860	0.9962	0.9911
0.0775	0.7337	2000	0.1155	0.9787	0.9961	0.9723	0.9840
0.0751	0.9171	2500	0.0530	0.9901	0.9945	0.9908	0.9926
0.033	1.1005	3000	0.0505	0.9930	0.9956	0.9940	0.9948
0.0403	1.2839	3500	0.0447	0.9905	0.9908	0.9951	0.9929
0.0395	1.4674	4000	0.0857	0.9868	0.9967	0.9837	0.9901
0.0077	1.6508	4500	0.0708	0.9912	0.9903	0.9967	0.9935
0.0342	1.8342	5000	0.0945	0.9890	0.9962	0.9875	0.9918

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.19.1