bert-base-finetuned-sts-v3

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

• Loss: 0.3716
• Pearsonr: 0.9172

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: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Pearsonr
0.2265	1.0	2917	0.4886	0.8933
0.1504	2.0	5834	0.4374	0.8948
0.0982	3.0	8751	0.5246	0.8957
0.0832	4.0	11668	0.4387	0.9006
0.0751	5.0	14585	0.4036	0.9049
0.0564	6.0	17502	0.3828	0.9133
0.0488	7.0	20419	0.3716	0.9172
0.0384	8.0	23336	0.4060	0.9093
0.0365	9.0	26253	0.3939	0.9065
0.0319	10.0	29170	0.3953	0.9106
0.0262	11.0	32087	0.3885	0.9109
0.0219	12.0	35004	0.3724	0.9154
0.0188	13.0	37921	0.3827	0.9111
0.0175	14.0	40838	0.4103	0.9099
0.0144	15.0	43755	0.3768	0.9152
0.0132	16.0	46672	0.3868	0.9151
0.0125	17.0	49589	0.3981	0.9103
0.0106	18.0	52506	0.3808	0.9138
0.0095	19.0	55423	0.3904	0.9128
0.0089	20.0	58340	0.3885	0.9137

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0
• Datasets 2.7.1
• Tokenizers 0.13.2