| | --- |
| | library_name: transformers |
| | base_model: monologg/koelectra-small-finetuned-sentiment |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: koelectra_emotion_v2_2 |
| | 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. --> |
| |
|
| | # koelectra_emotion_v2_2 |
| | |
| | This model is a fine-tuned version of [monologg/koelectra-small-finetuned-sentiment](https://huggingface.co/monologg/koelectra-small-finetuned-sentiment) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.4392 |
| | - Accuracy: 0.5249 |
| | - F1: 0.5227 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| |
| | | 1.8251 | 1.0 | 601 | 1.7175 | 0.3130 | 0.2585 | |
| | | 1.6569 | 2.0 | 1202 | 1.5616 | 0.4007 | 0.3821 | |
| | | 1.5086 | 3.0 | 1803 | 1.4698 | 0.4397 | 0.4258 | |
| | | 1.4099 | 4.0 | 2404 | 1.4268 | 0.4661 | 0.4592 | |
| | | 1.3318 | 5.0 | 3005 | 1.3885 | 0.4779 | 0.4770 | |
| | | 1.2688 | 6.0 | 3606 | 1.3679 | 0.4927 | 0.4849 | |
| | | 1.2213 | 7.0 | 4207 | 1.3497 | 0.5071 | 0.5015 | |
| | | 1.1756 | 8.0 | 4808 | 1.3405 | 0.5144 | 0.5099 | |
| | | 1.1328 | 9.0 | 5409 | 1.3548 | 0.5162 | 0.5125 | |
| | | 1.0964 | 10.0 | 6010 | 1.3864 | 0.5151 | 0.5081 | |
| | | 1.0675 | 11.0 | 6611 | 1.3606 | 0.5198 | 0.5162 | |
| | | 1.0368 | 12.0 | 7212 | 1.3719 | 0.5195 | 0.5170 | |
| | | 1.0044 | 13.0 | 7813 | 1.3695 | 0.5256 | 0.5222 | |
| | | 0.9808 | 14.0 | 8414 | 1.3896 | 0.5216 | 0.5196 | |
| | | 0.9554 | 15.0 | 9015 | 1.4033 | 0.5228 | 0.5192 | |
| | | 0.9307 | 16.0 | 9616 | 1.4135 | 0.5247 | 0.5236 | |
| | | 0.9131 | 17.0 | 10217 | 1.4193 | 0.5198 | 0.5181 | |
| | | 0.8969 | 18.0 | 10818 | 1.4259 | 0.5276 | 0.5243 | |
| | | 0.8825 | 19.0 | 11419 | 1.4385 | 0.5245 | 0.5224 | |
| | | 0.8779 | 20.0 | 12020 | 1.4392 | 0.5249 | 0.5227 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.56.1 |
| | - Pytorch 2.8.0+cu126 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.22.0 |
| |
|
