metadata

base_model: ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep10
tags:
  - generated_from_trainer
datasets:
  - klue
metrics:
  - accuracy
  - f1
model-index:
  - name: nli_sts_roberta_large_lr1e-05_wd1e-03_ep10_lr1e-05_wd1e-03_ep10_ckpt
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: klue
          type: klue
          config: nli
          split: validation
          args: nli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8963333333333333
          - name: F1
            type: f1
            value: 0.8962457758881018

nli_sts_roberta_large_lr1e-05_wd1e-03_ep10_lr1e-05_wd1e-03_ep10_ckpt

This model is a fine-tuned version of ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep10 on the klue dataset. It achieves the following results on the evaluation set:

Loss: 0.6903
Accuracy: 0.8963
F1: 0.8962

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: 1e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6445	1.0	391	0.4254	0.852	0.8512
0.2943	2.0	782	0.3371	0.889	0.8886
0.1586	3.0	1173	0.3704	0.888	0.8881
0.0921	4.0	1564	0.4429	0.892	0.8919
0.0565	5.0	1955	0.4864	0.899	0.8989
0.0378	6.0	2346	0.5727	0.8963	0.8962
0.0238	7.0	2737	0.6247	0.8957	0.8955
0.016	8.0	3128	0.6578	0.8947	0.8945
0.0101	9.0	3519	0.6780	0.8953	0.8952
0.0067	10.0	3910	0.6903	0.8963	0.8962

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.13.0
Tokenizers 0.13.3