---
tags:
- generated_from_trainer
datasets:
- coco
metrics:
- rouge
- bleu
model-index:
- name: vit-swin-base-224-gpt2-image-captioning
  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-swin-base-224-gpt2-image-captioning

This model is a fine-tuned version of [](https://huggingface.co/) on the coco dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7923
- Rouge1: 41.8451
- Rouge2: 16.3493
- Rougel: 38.0288
- Rougelsum: 38.049
- Bleu: 10.2776
- Gen Len: 11.2946

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|
| 1.0018        | 0.38  | 2000  | 0.8860          | 38.6537 | 13.8145 | 35.3932 | 35.3935   | 8.2448  | 11.2946 |
| 0.8827        | 0.75  | 4000  | 0.8395          | 40.0458 | 14.8829 | 36.5321 | 36.5366   | 9.1169  | 11.2946 |
| 0.8378        | 1.13  | 6000  | 0.8140          | 41.2736 | 15.9576 | 37.5504 | 37.5512   | 9.871   | 11.2946 |
| 0.7913        | 1.51  | 8000  | 0.8012          | 41.6642 | 16.1987 | 37.8786 | 37.8891   | 10.0786 | 11.2946 |
| 0.7794        | 1.89  | 10000 | 0.7933          | 41.9119 | 16.3738 | 38.1062 | 38.1292   | 10.288  | 11.2946 |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2