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
Downloads last month
117
Safetensors
Model size
109M params
Tensor type
F32
·
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.

Model tree for gigauser/kcbert_nsmc_tuning

Base model

beomi/kcbert-base
Finetuned
(152)
this model

Dataset used to train gigauser/kcbert_nsmc_tuning

Evaluation results