metadata

license: apache-2.0
base_model: beomi/kcbert-base
tags:
  - generated_from_trainer
datasets:
  - nsmc
metrics:
  - accuracy
model-index:
  - name: kcbert_nsmc_tuning
    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: 0.90134

kcbert_nsmc_tuning

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

Loss: 0.4492
Accuracy: 0.9013

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1689	1.0	2344	0.2717	0.9006
0.0951	2.0	4688	0.3458	0.8995
0.051	3.0	7032	0.4492	0.9013

Framework versions

Transformers 4.42.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1