Downloads · 30 days
5
11% of all-time downloads
kobert_naver
memorygreen/kobert_naver
kobert_naver is a text classification model from memorygreen. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
44
Public
Parameters
92.2M
1.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors369 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Jun 17, 2026
- Updated
- Jun 22, 2026
- SHA
- bfa445a0
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
kobert_naver
This model is a fine-tuned version of monologg/kobert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6917
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6960 | 1.0 | 1000 | 0.6917 |
Framework versions
- Transformers 5.12.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jun 17, 2026
- Updated
- Jun 22, 2026