---
base_model: ddobokki/vision-encoder-decoder-vit-gpt2-coco-ko
tags:
- generated_from_trainer
model-index:
- name: BITAmin_Pet
  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

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:
- eval_loss: 0.1144
- eval_rouge1: 0.3019
- eval_rouge2: 0.0755
- eval_rougeL: 0.2642
- eval_rougeLsum: 0.3019
- eval_gen_len: 100.0
- eval_runtime: 1560.6796
- eval_samples_per_second: 0.849
- eval_steps_per_second: 0.425
- epoch: 2.0
- step: 11926

## 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

### Framework versions

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