metadata
library_name: transformers
language:
- ko
license: apache-2.0
base_model: monologg/koelectra-base-v3-discriminator
tags:
- text-classification
- KoELECTRA
- Korean-NLP
- topic-classification
- news-classification
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: data
results: []
data
This model is a fine-tuned version of monologg/koelectra-base-v3-discriminator on the klue-ynat dataset. It achieves the following results on the evaluation set:
- Loss: 0.4134
- Accuracy: 0.8585
- Precision: 0.8475
- Recall: 0.8743
- F1: 0.8600
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.4004 | 1.0 | 714 | 0.4290 | 0.8523 | 0.8334 | 0.8733 | 0.8515 |
| 0.3007 | 2.0 | 1428 | 0.4053 | 0.8547 | 0.8464 | 0.8730 | 0.8580 |
| 0.2274 | 3.0 | 2142 | 0.4134 | 0.8585 | 0.8475 | 0.8743 | 0.8600 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1