---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: vit
  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. -->

# vit

This model is a fine-tuned version of [nlpconnect/vit-gpt2-image-captioning](https://huggingface.co/nlpconnect/vit-gpt2-image-captioning) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2973
- Rouge1: 67.9673
- Rouge2: 58.9518
- Rougel: 67.1789
- Rougelsum: 67.324
- Bleu: 54.4707
- Gen Len: 7.7647

## 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: 4

### Training results



### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3