checkpoints

IshanWarshamana/checkpoints

checkpoints is a image-text-to-text model from IshanWarshamana. 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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Hugging Face

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At a glance

Task: Image-Text-to-Text
Library: transformers
Model type: vision-encoder-decoder
Access: Public
Created: Jul 7, 2024
Updated: Jul 17, 2024
SHA: a65ba0e9

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Base models

Model card

From the Hugging Face model README

TrOCR_Printed_Sinahala_1

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

Loss: 0.6949
Cer: 0.1689

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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.0989	0.0444	100	1.0041	0.1787
0.1265	0.0889	200	0.7479	0.2270
0.0302	0.1333	300	0.9396	0.1863
0.0483	0.1778	400	0.6949	0.1689
0.0637	0.2222	500	0.6022	0.1816
0.0726	0.2667	600	0.6801	0.2083
0.0169	0.3111	700	0.5828	0.1721
0.0084	0.3556	800	0.5437	0.1750
0.0239	0.4	900	0.5451	0.1744
0.0215	0.4444	1000	0.5470	0.1717

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

Task: Image-Text-to-Text
Library: transformers
Type: vision-encoder-decoder
Created: Jul 7, 2024
Updated: Jul 17, 2024