| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: monologg/koelectra-base-v3-discriminator |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: MyMbti_classification_model |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # MyMbti_classification_model |
| |
|
| | This model is a fine-tuned version of [monologg/koelectra-base-v3-discriminator](https://huggingface.co/monologg/koelectra-base-v3-discriminator) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.5286 |
| | - Accuracy: 0.1898 |
| | - F1: 0.1547 |
| |
|
| | ## Model description |
| |
|
| | ์ด ๋ชจ๋ธ์ 16๊ฐ์ MBTI๋ฅผ ๋ผ๋ฒจ๋ก ๋ถ๋ฅํด ํด๋น ๋ผ๋ฒจ์ ์์ธกํ๋ ๋ชจ๋ธ์
๋๋ค. |
| | ๋ชจ๋ธ์ ์ ํ๋๊ฐ ๋ฎ์๊ฒ์ ํ์ต์ ์ฌ์ฉํ ๋ฐ์ดํฐ๊ฐ ์ ์ ๋์ง ์์์ต๋๋ค. |
| | ํ
์คํธ์ฉ์ผ๋ก ๋ง๋ค์๊ธฐ ๋๋ฌธ์ ์ฑ๋ฅ์ ๋ณด์ฅํ์ง ๋ชปํฉ๋๋ค. |
| |
|
| | ## 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: 3e-05 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 32 |
| | - 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: 4 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| | |:-------------:|:------:|:-----:|:---------------:|:--------:|:------:| |
| | | 2.6213 | 0.1673 | 500 | 2.6180 | 0.1142 | 0.0241 | |
| | | 2.6412 | 0.3347 | 1000 | 2.6167 | 0.1318 | 0.0336 | |
| | | 2.5861 | 0.5020 | 1500 | 2.6111 | 0.1320 | 0.0385 | |
| | | 2.6183 | 0.6693 | 2000 | 2.6133 | 0.1222 | 0.0461 | |
| | | 2.5954 | 0.8367 | 2500 | 2.5958 | 0.1411 | 0.0607 | |
| | | 2.5828 | 1.0040 | 3000 | 2.5822 | 0.1479 | 0.0703 | |
| | | 2.5803 | 1.1714 | 3500 | 2.5685 | 0.1553 | 0.0826 | |
| | | 2.5615 | 1.3387 | 4000 | 2.5566 | 0.1645 | 0.0977 | |
| | | 2.5463 | 1.5060 | 4500 | 2.5531 | 0.1687 | 0.1111 | |
| | | 2.5511 | 1.6734 | 5000 | 2.5446 | 0.1679 | 0.1170 | |
| | | 2.5242 | 1.8407 | 5500 | 2.5342 | 0.1726 | 0.1215 | |
| | | 2.5191 | 2.0080 | 6000 | 2.5246 | 0.1825 | 0.1384 | |
| | | 2.4866 | 2.1754 | 6500 | 2.5306 | 0.1834 | 0.1428 | |
| | | 2.5005 | 2.3427 | 7000 | 2.5325 | 0.1803 | 0.1399 | |
| | | 2.5131 | 2.5100 | 7500 | 2.5195 | 0.1877 | 0.1473 | |
| | | 2.4918 | 2.6774 | 8000 | 2.5204 | 0.1876 | 0.1489 | |
| | | 2.4755 | 2.8447 | 8500 | 2.5218 | 0.1877 | 0.1568 | |
| | | 2.4223 | 3.0120 | 9000 | 2.5286 | 0.1898 | 0.1547 | |
| | | 2.4297 | 3.1794 | 9500 | 2.5364 | 0.1874 | 0.1599 | |
| | | 2.4213 | 3.3467 | 10000 | 2.5432 | 0.1866 | 0.1584 | |
| | | 2.4619 | 3.5141 | 10500 | 2.5393 | 0.1879 | 0.1585 | |
| | | 2.4383 | 3.6814 | 11000 | 2.5424 | 0.1849 | 0.1590 | |
| | | 2.4368 | 3.8487 | 11500 | 2.5414 | 0.1866 | 0.1599 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.55.2 |
| | - Pytorch 2.8.0+cu126 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.21.4 |
| | |
