beit-base-patch16-224-pt22k-ft22k-finetuned-plantorgans

farmaieu/beit-base-patch16-224-pt22k-ft22k-finetuned-plantorgans

beit-base-patch16-224-pt22k-ft22k-finetuned-plantorgans is a image segmentation model from farmaieu. Use it for the image segmentation 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 apache-2.0.

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

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At a glance

Task: Image Segmentation
Library: transformers
License: apache-2.0
Model type: beit
Access: Public
Created: Mar 9, 2024
Updated: Mar 9, 2024
SHA: 7679cb6e

Base models

microsoft/beit-base-patch16-224-pt22k-ft22k

Model card

From the Hugging Face model README

beit-base-patch16-224-pt22k-ft22k-finetuned-plantorgans

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the jpodivin/plantorgans dataset. It achieves the following results on the evaluation set:

Loss: 1.2004
Mean Iou: 0.0260
Mean Accuracy: 0.0325
Overall Accuracy: 0.0435
Accuracy Void: nan
Accuracy Fruit: 0.1299
Accuracy Leaf: 0.0
Accuracy Flower: 0.0
Accuracy Stem: 0.0001
Iou Void: 0.0
Iou Fruit: 0.1299
Iou Leaf: 0.0
Iou Flower: 0.0
Iou Stem: 0.0001

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: 10
eval_batch_size: 10
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Void	Accuracy Fruit	Accuracy Leaf	Accuracy Stem	Iou Fruit	Iou Leaf	Iou Stem
1.0657	1.0	575	1.1178	0.0158	0.0197	0.0261	nan	0.0776	0.0	0.0012	0.0776	0.0	0.0012
0.5398	2.0	1150	1.0816	0.0361	0.0451	0.0599	nan	0.1783	0.0000	0.0020	0.1783	0.0000	0.0020
0.4794	3.0	1725	1.2122	0.0110	0.0138	0.0179	nan	0.0517	0.0003	0.0032	0.0517	0.0003	0.0032
0.446	4.0	2300	1.3138	0.0114	0.0142	0.0189	nan	0.0562	0.0	0.0006	0.0562	0.0	0.0006
0.4422	5.0	2875	1.2360	0.0005	0.0006	0.0006	nan	0.0012	0.0	0.0013	0.0012	0.0	0.0013
0.4183	6.0	3450	1.3598	0.0177	0.0221	0.0296	nan	0.0885	0.0	0.0	0.0885	0.0	0.0
0.3921	7.0	4025	1.2523	0.0267	0.0333	0.0446	nan	0.1333	0.0000	0.0	0.1333	0.0000	0.0
0.3743	8.0	4600	1.3146	0.0401	0.0502	0.0670	nan	0.2002	0.0	0.0005	0.2001	0.0	0.0005
0.3695	9.0	5175	1.2873	0.0294	0.0368	0.0492	nan	0.1472	0.0	0.0001	0.1471	0.0	0.0001
0.3796	10.0	5750	1.2004	0.0260	0.0325	0.0435	nan	0.1299	0.0	0.0001	0.1299	0.0	0.0001

Framework versions

Transformers 4.38.0.dev0
Pytorch 2.1.2+cu121
Datasets 2.16.1
Tokenizers 0.15.0

Task: Image Segmentation
Library: transformers
Type: beit
License: apache-2.0
Created: Mar 9, 2024
Updated: Mar 9, 2024