---
tags:
- generated_from_trainer
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Rouge1: 99.2148
- Rouge2: 99.1824
- Rougel: 99.22
- Rougelsum: 99.2169
- Bleu: 96.4656
- Gen Len: 10.4161

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|
| 0.622         | 11.36 | 2000 | 0.0330          | 91.0769 | 88.8333 | 90.7025 | 90.7277   | 84.8472 | 10.4161 |
| 0.0547        | 22.73 | 4000 | 0.0015          | 99.0694 | 98.9636 | 99.0615 | 99.0613   | 96.1312 | 10.4161 |
| 0.0238        | 34.09 | 6000 | 0.0007          | 99.1681 | 99.0942 | 99.167  | 99.1646   | 96.3754 | 10.4161 |
| 0.0046        | 45.45 | 8000 | 0.0001          | 99.2225 | 99.1781 | 99.217  | 99.2171   | 96.4412 | 10.4161 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0