ViT-GPT2-Image_Captioning_model

mo-thecreator/ViT-GPT2-Image_Captioning_model

ViT-GPT2-Image_Captioning_model is a image-to-text model from mo-thecreator. Use it when you need a caption or text from an image. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Image-to-Text
Library: transformers
Model type: vision-encoder-decoder
Access: Public
Created: Sep 29, 2024
Updated: Sep 30, 2024
SHA: cb6dbf1c

Model card

From the Hugging Face model README

ViT-GPT2

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.4134
Rouge2 Fmeasure: 0.1166

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge2 Fmeasure
No log	0.9987	496	2.4901	0.1077
2.5089	1.9995	993	2.4292	0.1141
2.4103	2.9962	1488	2.4134	0.1166

Framework versions

Transformers 4.44.2
Pytorch 2.4.0
Datasets 3.0.0
Tokenizers 0.19.1

Task: Image-to-Text
Library: transformers
Type: vision-encoder-decoder
Created: Sep 29, 2024
Updated: Sep 30, 2024