---
license: mit
base_model: beomi/KcELECTRA-base-v2022
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: KcELECTRA-base-v2022-KEmoFact-0925
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# KcELECTRA-base-v2022-KEmoFact-0925

This model is a fine-tuned version of [beomi/KcELECTRA-base-v2022](https://huggingface.co/beomi/KcELECTRA-base-v2022) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0671
- Precision: 0.2272
- Recall: 0.2813
- F1: 0.2514
- Accuracy: 0.7244
- Jaccard Scores: 0.7016
- Cls Accuracy: 0.6433

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Jaccard Scores | Cls Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:--------------:|:------------:|
| No log        | 1.0   | 414  | 1.0860          | 0.1223    | 0.1235 | 0.1229 | 0.7113   | 0.5185         | 0.4574       |
| 1.405         | 2.0   | 828  | 0.9584          | 0.1670    | 0.2076 | 0.1851 | 0.7275   | 0.6476         | 0.6001       |
| 0.8557        | 3.0   | 1242 | 0.9666          | 0.1887    | 0.2312 | 0.2078 | 0.7286   | 0.6656         | 0.6134       |
| 0.6123        | 4.0   | 1656 | 1.0142          | 0.2122    | 0.2538 | 0.2311 | 0.7321   | 0.6794         | 0.6346       |
| 0.4582        | 5.0   | 2070 | 1.0391          | 0.2069    | 0.2549 | 0.2284 | 0.7260   | 0.6787         | 0.6358       |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3