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deberta-korean-multilabel_base-lora
yj512/deberta-korean-multilabel_base-lora
deberta-korean-multilabel_base-lora is a machine learning model from yj512. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Jan 13, 2026
- Updated
- Jan 13, 2026
- SHA
- a4570c27
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. -->
deberta-korean-multilabel_base-lora
This model is a fine-tuned version of team-lucid/deberta-v3-base-korean on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1443
- F1: 0.9717
- Roc Auc: 0.8439
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: 0.0002
- train_batch_size: 64
- eval_batch_size: 128
- 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc |
|---|---|---|---|---|---|
| 0.1514 | 1.0 | 6259 | 0.1509 | 0.9705 | 0.8375 |
| 0.1396 | 2.0 | 12518 | 0.1443 | 0.9717 | 0.8439 |
Framework versions
- PEFT 0.18.0
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
- Library
- peft
- License
- apache-2.0
- Created
- Jan 13, 2026
- Updated
- Jan 13, 2026