---
license: apache-2.0
tags:
- generated_from_trainer
base_model: nlpconnect/vit-gpt2-image-captioning
model-index:
- name: Vit-GPT2-COCO2017Flickr-40k-04
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Vit-GPT2-COCO2017Flickr-40k-04

This model is a fine-tuned version of [nlpconnect/vit-gpt2-image-captioning](https://huggingface.co/nlpconnect/vit-gpt2-image-captioning) on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.4650
- eval_rouge1: 42.848 
- eval_rouge2: 17.6905
- eval_rougeL: 36.5451
- eval_rougeLsum: 38.9854
- eval_gen_len: 12.025
- eval_samples_per_second: 7.371
- eval_steps_per_second: 1.843
- epoch: 1.4
- step: 7000

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.1497        | 0.1   | 500   | 0.5462          | 40.1774 | 14.6199 | 36.3335 | 36.3518   | 12.5965 |
| 0.1604        | 0.2   | 1000  | 0.5302          | 41.4714 | 16.0237 | 37.5992 | 37.5915   | 11.914  |
| 0.1631        | 0.3   | 1500  | 0.5436          | 40.3816 | 14.6958 | 36.6109 | 36.6027   | 12.3295 |
| 0.1634        | 0.4   | 2000  | 0.5266          | 40.9484 | 15.9068 | 37.5194 | 37.5088   | 12.033  |
| 0.1576        | 0.5   | 2500  | 0.5544          | 40.373  | 15.012  | 36.5218 | 36.5141   | 12.3345 |
| 0.1599        | 0.6   | 3000  | 0.5425          | 40.7552 | 15.2754 | 37.1059 | 37.1299   | 12.191  |
| 0.291         | 0.7   | 3500  | 0.4545          | 41.5934 | 16.251  | 37.7291 | 37.7113   | 12.0295 |
| 0.2825        | 0.8   | 4000  | 0.4558          | 42.6728 | 17.1703 | 38.8692 | 38.8841   | 12.246  |
| 0.2737        | 0.9   | 4500  | 0.4565          | 43.0036 | 16.8421 | 39.1761 | 39.1693   | 11.7975 |
| 0.2683        | 1.0   | 5000  | 0.4576          | 42.1341 | 16.7973 | 38.2881 | 38.3083   | 11.8655 |
| 0.1687        | 1.1   | 5500  | 0.4996          | 41.7152 | 16.4042 | 37.7724 | 37.7629   | 12.384  |
| 0.168         | 1.2   | 6000  | 0.5046          | 41.6521 | 16.6159 | 37.7915 | 37.7778   | 12.661  |
| 0.1688        | 1.3   | 6500  | 0.5020          | 42.3292 | 17.1408 | 38.5407 | 38.5282   | 11.846  |
| 0.1682        | 1.4   | 7000  | 0.5045          | 42.848  | 17.6905 | 38.9854 | 38.9896   | 12.025  |
### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2