---
library_name: transformers
base_model: monologg/koelectra-small-finetuned-sentiment
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: koelectra_emotion_v2
  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

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: 1.4260
- 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