---
license: apache-2.0
base_model: nlpconnect/vit-gpt2-image-captioning
tags:
- generated_from_trainer
model-index:
- name: vit-gpt-person-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-gpt-person-image-captioning

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:
- Loss: 0.0173

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.9984 | 312  | 0.0211          |
| 0.0609        | 2.0    | 625  | 0.0194          |
| 0.0609        | 2.9984 | 937  | 0.0183          |
| 0.021         | 4.0    | 1250 | 0.0176          |
| 0.0194        | 4.992  | 1560 | 0.0173          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1