---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: VIT_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_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: 2.0461
- Rouge1: 0.4850
- Rouge2: 0.2566
- Rougel: 0.3589
- Rougelsum: 0.3595

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1024
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.4042        | 1.0   | 1828  | 1.7451          | 0.4622 | 0.1906 | 0.3370 | 0.3422    |
| 1.5875        | 2.0   | 3656  | 1.5933          | 0.4599 | 0.2060 | 0.3451 | 0.3472    |
| 1.3882        | 3.0   | 5484  | 1.5322          | 0.4606 | 0.2082 | 0.3422 | 0.3442    |
| 1.2415        | 4.0   | 7312  | 1.5130          | 0.4687 | 0.2208 | 0.3458 | 0.3476    |
| 1.1113        | 5.0   | 9140  | 1.5186          | 0.4630 | 0.2146 | 0.3398 | 0.3402    |
| 0.9671        | 6.0   | 10968 | 1.5683          | 0.4720 | 0.2290 | 0.3517 | 0.3520    |
| 0.8528        | 7.0   | 12796 | 1.6352          | 0.4704 | 0.2281 | 0.3491 | 0.3496    |
| 0.7555        | 8.0   | 14624 | 1.7122          | 0.4725 | 0.2305 | 0.3477 | 0.3481    |
| 0.6567        | 9.0   | 16452 | 1.7814          | 0.4763 | 0.2389 | 0.3537 | 0.3543    |
| 0.5612        | 10.0  | 18280 | 1.8528          | 0.4777 | 0.2410 | 0.3515 | 0.3516    |
| 0.4953        | 11.0  | 20108 | 1.9072          | 0.4799 | 0.2487 | 0.3562 | 0.3565    |
| 0.4445        | 12.0  | 21936 | 1.9503          | 0.4829 | 0.2514 | 0.3571 | 0.3574    |
| 0.3976        | 13.0  | 23764 | 1.9928          | 0.4834 | 0.2543 | 0.3569 | 0.3573    |
| 0.3643        | 14.0  | 25592 | 2.0249          | 0.4820 | 0.2520 | 0.3575 | 0.3581    |
| 0.3263        | 15.0  | 27420 | 2.0461          | 0.4850 | 0.2566 | 0.3589 | 0.3595    |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3