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metadata
base_model: ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep5
tags:
  - generated_from_trainer
datasets:
  - klue
metrics:
  - accuracy
  - f1
model-index:
  - name: nli_sts_roberta_large_lr1e_05_wd1e_03_ep5_lr1e-05_wd1e-03_ep5_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: 0.8986666666666666
          - name: F1
            type: f1
            value: 0.8985280502079203

nli_sts_roberta_large_lr1e_05_wd1e_03_ep5_lr1e-05_wd1e-03_ep5_ckpt

This model is a fine-tuned version of ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep5 on the klue dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4971
  • Accuracy: 0.8987
  • F1: 0.8985

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: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.5471 1.0 391 0.3522 0.876 0.8756
0.2379 2.0 782 0.3345 0.8983 0.8981
0.1215 3.0 1173 0.3708 0.8997 0.8995
0.0661 4.0 1564 0.4734 0.896 0.8958
0.0407 5.0 1955 0.4971 0.8987 0.8985

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.13.0
  • Tokenizers 0.13.3