---
library_name: transformers
license: apache-2.0
base_model: nlpconnect/vit-gpt2-image-captioning
tags:
- generated_from_trainer
model-index:
- name: vit-gpt2-rocov22-ct-finetuned
  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-gpt2-rocov22-ct-finetuned

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: 1.3215

## 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 OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4502        | 1.0   | 1440 | 1.4252          |
| 1.392         | 2.0   | 2880 | 1.3534          |
| 1.2814        | 3.0   | 4320 | 1.3246          |
| 1.22          | 4.0   | 5760 | 1.3164          |
| 1.1829        | 5.0   | 7200 | 1.3215          |


### Framework versions

- Transformers 4.56.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0