metadata

license: cc-by-sa-4.0
tags:
  - generated_from_trainer
datasets:
  - klue
metrics:
  - pearsonr
base_model: klue/bert-base
model-index:
  - name: bert-base-finetuned-sts-v3
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: klue
          type: klue
          config: sts
          split: train
          args: sts
        metrics:
          - type: pearsonr
            value: 0.9172194083849969
            name: Pearsonr

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