PolizzeDonut-Cluster3di3-AutoEnc-3Epochs

tedad09/PolizzeDonut-Cluster3di3-AutoEnc-3Epochs

PolizzeDonut-Cluster3di3-AutoEnc-3Epochs is a image-text-to-text model from tedad09. 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. The card lists the license as mit.

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

Downloads · 30 days

18% of all-time downloads

All-time downloads

Public

Parameters

202M

1.6 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors809 MB · 100%

Parameter types

How the weights are stored.

F32202M · 100%

Try a prompt

Base models

tedad09/PolizzeDonut-SoloPDF-3Epochs-tot

Datasets

imagefolder

Model card

From the Hugging Face model README

PolizzeDonut-Cluster3di3-AutoEnc-3Epochs

This model is a fine-tuned version of tedad09/PolizzeDonut-SoloPDF-3Epochs-tot on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 1.4445

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.9648	1.0	104	1.5477
0.7524	2.0	208	1.4673
0.6669	3.0	312	1.4445

Framework versions

Transformers 4.38.2
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Task: Image-Text-to-Text
Library: transformers
Type: vision-encoder-decoder
License: mit
Created: Mar 28, 2024
Updated: Mar 28, 2024