vit_gpt2_latex

fklska/vit_gpt2_latex

vit_gpt2_latex is a image-text-to-text model from fklska. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. 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-Text-to-Text
Library: transformers
Model type: vision-encoder-decoder
Access: Public
Created: Jun 5, 2026
Updated: Jun 5, 2026
SHA: 9e921e70

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Model card

From the Hugging Face model README

vit_gpt2_latex

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

Loss: 1.7162

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: 16
eval_batch_size: 16
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
training_steps: 1500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.5072	1.0	699	1.9415
1.1143	2.0	1398	1.7180
1.0090	2.1459	1500	1.7162

Framework versions

Transformers 5.9.0
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2

Task: Image-Text-to-Text
Library: transformers
Type: vision-encoder-decoder
Created: Jun 5, 2026
Updated: Jun 5, 2026