---
base_model: monologg/koelectra-small-v3-discriminator
tags:
- generated_from_trainer
datasets:
- generator
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: chkpt
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: generator
      type: generator
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8826086956521739
    - name: F1
      type: f1
      value: 0.8275730495029622
    - name: Precision
      type: precision
      value: 0.7789981096408317
    - name: Recall
      type: recall
      value: 0.8826086956521739
---

<!-- 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. -->

# chkpt

This model is a fine-tuned version of [monologg/koelectra-small-v3-discriminator](https://huggingface.co/monologg/koelectra-small-v3-discriminator) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2815
- Accuracy: 0.8826
- F1: 0.8276
- Precision: 0.7790
- Recall: 0.8826

## 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: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 29   | 1.2815          | 0.8826   | 0.8276 | 0.7790    | 0.8826 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.15.0