Downloads · 30 days
12
32% of all-time downloads
koelectra_emotion_v2
be2be2/koelectra_emotion_v2
koelectra_emotion_v2 is a text classification model from be2be2. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
38
Public
Parameters
13.8M
110 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors55.1 MB · 98%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- electra
- Access
- Public
- Created
- Sep 28, 2025
- Updated
- Sep 29, 2025
- SHA
- 21de2da4
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. -->
koelectra_emotion_v2
This model is a fine-tuned version of monologg/koelectra-small-finetuned-sentiment on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4260
- Accuracy: 0.6118
- F1: 0.6172
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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.5444 | 1.0 | 601 | 1.3725 | 0.4626 | 0.4567 |
| 1.218 | 2.0 | 1202 | 1.2090 | 0.5664 | 0.5693 |
| 1.0556 | 3.0 | 1803 | 1.1186 | 0.6031 | 0.6075 |
| 0.9497 | 4.0 | 2404 | 1.1470 | 0.5981 | 0.6056 |
| 0.8734 | 5.0 | 3005 | 1.1450 | 0.6005 | 0.6067 |
| 0.808 | 6.0 | 3606 | 1.1479 | 0.6136 | 0.6181 |
| 0.7489 | 7.0 | 4207 | 1.1225 | 0.6287 | 0.6348 |
| 0.6926 | 8.0 | 4808 | 1.2075 | 0.6096 | 0.6177 |
| 0.6472 | 9.0 | 5409 | 1.2047 | 0.6180 | 0.6227 |
| 0.6028 | 10.0 | 6010 | 1.2248 | 0.6194 | 0.6249 |
| 0.5624 | 11.0 | 6611 | 1.2474 | 0.6154 | 0.6215 |
| 0.5303 | 12.0 | 7212 | 1.2627 | 0.6203 | 0.6257 |
| 0.4956 | 13.0 | 7813 | 1.2977 | 0.6191 | 0.6245 |
| 0.4662 | 14.0 | 8414 | 1.3655 | 0.6081 | 0.6144 |
| 0.4439 | 15.0 | 9015 | 1.3801 | 0.6067 | 0.6124 |
| 0.4221 | 16.0 | 9616 | 1.3854 | 0.6124 | 0.6167 |
| 0.4097 | 17.0 | 10217 | 1.4101 | 0.6105 | 0.6164 |
| 0.3921 | 18.0 | 10818 | 1.4359 | 0.6054 | 0.6109 |
| 0.3799 | 19.0 | 11419 | 1.4269 | 0.6111 | 0.6169 |
| 0.369 | 20.0 | 12020 | 1.4260 | 0.6118 | 0.6172 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
- Task
- Text Classification
- Library
- transformers
- Type
- electra
- Created
- Sep 28, 2025
- Updated
- Sep 29, 2025