---
license: apache-2.0
base_model: monologg/koelectra-base-v3-discriminator
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: koelectra-base-v3-discriminator-KEmoFact-0925
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# koelectra-base-v3-discriminator-KEmoFact-0925

This model is a fine-tuned version of [monologg/koelectra-base-v3-discriminator](https://huggingface.co/monologg/koelectra-base-v3-discriminator) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0290
- Precision: 0.1739
- Recall: 0.2415
- F1: 0.2022
- Accuracy: 0.7191
- Jaccard Scores: 0.6892
- Cls Accuracy: 0.6197

## 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  | 1.1425          | 0.0698    | 0.0726 | 0.0711 | 0.7029   | 0.4752         | 0.4204       |
| 1.4439        | 2.0   | 828  | 1.0332          | 0.1119    | 0.1676 | 0.1342 | 0.7112   | 0.6452         | 0.5753       |
| 0.9159        | 3.0   | 1242 | 0.9799          | 0.1438    | 0.1912 | 0.1642 | 0.7302   | 0.6322         | 0.5977       |
| 0.6814        | 4.0   | 1656 | 1.0124          | 0.1512    | 0.2064 | 0.1745 | 0.7265   | 0.6575         | 0.6189       |
| 0.538         | 5.0   | 2070 | 1.0331          | 0.1582    | 0.2199 | 0.1840 | 0.7205   | 0.6682         | 0.6195       |


### Framework versions

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