---
base_model: ddobokki/vision-encoder-decoder-vit-gpt2-coco-ko
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: BITAMIN_PET_FINAL
  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. -->

# BITAMIN_PET_FINAL

This model is a fine-tuned version of [ddobokki/vision-encoder-decoder-vit-gpt2-coco-ko](https://huggingface.co./ddobokki/vision-encoder-decoder-vit-gpt2-coco-ko) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0670
- Rouge1: 5.1373
- Rouge2: 3.2797
- Rougel: 5.1561
- Rougelsum: 5.1999
- Gen Len: 100.0

## 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: 2
- eval_batch_size: 2
- 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  | Gen Len | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:-------:|:---------------:|:------:|:------:|:------:|:---------:|
| 0.1753        | 1.0   | 5963  | 100.0   | 0.1586          | 0.0    | 0.0    | 0.0    | 0.0       |
| 0.1066        | 2.0   | 11926 | 0.1091  | 0.2155          | 0.1961 | 0.2155 | 0.2305 | 100.0     |
| 0.0659        | 3.0   | 17889 | 0.0834  | 1.8169          | 1.2573 | 1.8423 | 1.8571 | 100.0     |
| 0.0417        | 4.0   | 23852 | 0.0712  | 2.9034          | 1.9182 | 2.9223 | 2.9168 | 100.0     |
| 0.0319        | 5.0   | 29815 | 0.0670  | 5.1373          | 3.2797 | 5.1561 | 5.1999 | 100.0     |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1