README.md

metadata

license: cc-by-sa-4.0
tags:
  - generated_from_trainer
datasets:
  - nsmc
metrics:
  - accuracy
  - f1
model-index:
  - name: klue_bert_base
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: nsmc
          type: nsmc
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.90564
          - name: F1
            type: f1
            value: 0.9056337214649489

klue_bert_base

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

• Loss: 0.2415
• Accuracy: 0.9056
• F1: 0.9056

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.2742	1.0	2344	0.2381	0.9005	0.9005
0.1865	2.0	4688	0.2415	0.9056	0.9056

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.9.0
• Tokenizers 0.13.2