---
license: mit
base_model: gogamza/kobart-summarization
tags:
- generated_from_trainer
model-index:
- name: summary
  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. -->

# summary

This model is a fine-tuned version of [gogamza/kobart-summarization](https://huggingface.co./gogamza/kobart-summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3772

## 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4775        | 1.42  | 500  | 0.3851          |
| 0.2468        | 2.85  | 1000 | 0.3772          |
| 0.1299        | 4.27  | 1500 | 0.4203          |
| 0.0721        | 5.7   | 2000 | 0.4461          |
| 0.0425        | 7.12  | 2500 | 0.4582          |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0