---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: KoELECTRA-small-v3-modu-ner
  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-small-v3-modu-ner

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1443
- Precision: 0.8176
- Recall: 0.8401
- F1: 0.8287
- Accuracy: 0.9615

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 3787
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 3788  | 0.1511          | 0.8095    | 0.8257 | 0.8176 | 0.9594   |
| No log        | 2.0   | 7576  | 0.1461          | 0.8121    | 0.8339 | 0.8228 | 0.9600   |
| No log        | 3.0   | 11364 | 0.1417          | 0.8139    | 0.8372 | 0.8254 | 0.9607   |
| No log        | 4.0   | 15152 | 0.1418          | 0.8238    | 0.8346 | 0.8292 | 0.9617   |
| 0.0748        | 5.0   | 18940 | 0.1443          | 0.8176    | 0.8401 | 0.8287 | 0.9615   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2