---
library_name: transformers
base_model: eenzeenee/t5-base-korean-summarization
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: news_summarization_model
  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. -->

# news_summarization_model

This model is a fine-tuned version of [eenzeenee/t5-base-korean-summarization](https://huggingface.co/eenzeenee/t5-base-korean-summarization) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2221
- Rouge1: 0.6031
- Rouge2: 0.4193
- Rougel: 0.5896
- Rougelsum: 0.5892
- Gen Len: 42.2714

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.523         | 0.4762 | 100  | 0.3847          | 0.4833 | 0.2872 | 0.4627 | 0.4654    | 41.7571 |
| 0.3377        | 0.9524 | 200  | 0.2590          | 0.5709 | 0.3929 | 0.5581 | 0.5564    | 41.7810 |
| 0.2641        | 1.4286 | 300  | 0.2334          | 0.5889 | 0.4018 | 0.5785 | 0.5781    | 42.5048 |
| 0.2361        | 1.9048 | 400  | 0.2221          | 0.6031 | 0.4193 | 0.5896 | 0.5892    | 42.2714 |


### Framework versions

- Transformers 4.55.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4