---
base_model: ddobokki/vision-encoder-decoder-vit-gpt2-coco-ko
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Bitamin_mutimodal
  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_mutimodal

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: 0.0644
- Rouge1: 6.6906
- Rouge2: 3.2986
- Rougel: 6.6499
- Rougelsum: 6.6803
- 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: 4
- eval_batch_size: 4
- 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.2001        | 1.0   | 2982  | 0.1589          | 0.0    | 0.0    | 0.0    | 0.0       | 100.0   |
| 0.1178        | 2.0   | 5964  | 0.1095          | 0.8554 | 0.7275 | 0.8315 | 0.8554    | 100.0   |
| 0.0778        | 3.0   | 8946  | 0.0829          | 2.7168 | 1.6458 | 2.7157 | 2.6864    | 100.0   |
| 0.0552        | 4.0   | 11928 | 0.0691          | 5.454  | 2.6068 | 5.4184 | 5.4101    | 100.0   |
| 0.0396        | 5.0   | 14910 | 0.0644          | 6.6906 | 3.2986 | 6.6499 | 6.6803    | 100.0   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1