test-carbonate-segmentation2

edwardhuang/test-carbonate-segmentation2

test-carbonate-segmentation2 is a image segmentation model from edwardhuang. 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 other.

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

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At a glance

Task: Image Segmentation
Library: transformers
License: other
Model type: segformer
Access: Public
Created: May 25, 2023
Updated: May 25, 2023
SHA: a7a56110

Model card

From the Hugging Face model README

test-carbonate-segmentation2

This model is a fine-tuned version of nvidia/mit-b0 on the edwardhuang/carbonate-thin-sections dataset. It achieves the following results on the evaluation set:

Loss: 0.3642
Mean Iou: 0.2180
Mean Accuracy: 0.3344
Overall Accuracy: 0.6454
Accuracy Micrite: nan
Accuracy Cement: nan
Accuracy Peloid/pellet/ooid: nan
Accuracy Biotic: 0.6660
Accuracy Scale bar: 0.0028
Iou Micrite: 0.0
Iou Cement: nan
Iou Peloid/pellet/ooid: nan
Iou Biotic: 0.6511
Iou Scale bar: 0.0028

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: 6e-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: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Micrite	Accuracy Cement	Accuracy Peloid/pellet/ooid	Accuracy Biotic	Accuracy Scale bar	Iou Cement	Iou Peloid/pellet/ooid	Iou Biotic	Iou Scale bar
1.2003	2.22	20	1.5260	0.4834	0.7334	0.9835	nan	nan	nan	1.0	0.4669	nan	nan	0.9834	0.4669
1.2006	4.44	40	0.8923	0.6346	0.9521	0.9498	nan	nan	nan	0.9497	0.9545	nan	nan	0.9494	0.9545
1.4233	6.67	60	1.0240	0.4417	0.6716	0.9793	nan	nan	nan	0.9995	0.3438	nan	nan	0.9814	0.3438
1.1735	8.89	80	0.7964	0.5230	0.7890	0.9437	nan	nan	nan	0.9539	0.6241	nan	nan	0.9449	0.6241
1.0242	11.11	100	0.8747	0.5322	0.8038	0.9849	nan	nan	nan	0.9969	0.6108	nan	nan	0.9859	0.6108
0.9161	13.33	120	0.9217	0.5133	0.7767	0.9831	nan	nan	nan	0.9967	0.5568	nan	nan	0.9832	0.5568
0.8102	15.56	140	0.7069	0.5923	0.8907	0.9490	nan	nan	nan	0.9529	0.8286	nan	nan	0.9484	0.8286
0.5436	17.78	160	0.5149	0.3206	0.4929	0.8806	nan	nan	nan	0.9062	0.0795	nan	nan	0.8823	0.0795
0.8517	20.0	180	0.5646	0.3748	0.5719	0.9200	nan	nan	nan	0.9430	0.2008	nan	nan	0.9236	0.2008
0.4532	22.22	200	0.6128	0.3133	0.4837	0.9188	nan	nan	nan	0.9475	0.0199	nan	nan	0.9201	0.0199
1.3133	24.44	220	0.3006	0.2391	0.3645	0.7064	nan	nan	nan	0.7290	0.0	nan	nan	0.7172	0.0
0.4636	26.67	240	0.3260	0.1903	0.2901	0.5259	nan	nan	nan	0.5414	0.0388	nan	nan	0.5320	0.0388
0.9843	28.89	260	0.3663	0.2741	0.4182	0.6986	nan	nan	nan	0.7171	0.1193	nan	nan	0.7031	0.1193
0.7617	31.11	280	0.3338	0.2357	0.3627	0.7030	nan	nan	nan	0.7255	0.0	nan	nan	0.7072	0.0
1.283	33.33	300	0.3395	0.2723	0.4176	0.7232	nan	nan	nan	0.7434	0.0919	nan	nan	0.7250	0.0919
0.6578	35.56	320	0.3382	0.2069	0.3170	0.6143	nan	nan	nan	0.6339	0.0	nan	nan	0.6207	0.0
0.2129	37.78	340	0.3436	0.2288	0.3525	0.6831	nan	nan	nan	0.7049	0.0	nan	nan	0.6863	0.0
0.7001	40.0	360	0.2998	0.2001	0.3069	0.5771	nan	nan	nan	0.5950	0.0189	nan	nan	0.5813	0.0189
0.3866	42.22	380	0.3162	0.1840	0.2819	0.5464	nan	nan	nan	0.5639	0.0	nan	nan	0.5521	0.0
1.2623	44.44	400	0.3431	0.2125	0.3254	0.6172	nan	nan	nan	0.6365	0.0142	nan	nan	0.6234	0.0142
0.6115	46.67	420	0.2987	0.2020	0.3095	0.5998	nan	nan	nan	0.6190	0.0	nan	nan	0.6060	0.0
0.5802	48.89	440	0.3642	0.2180	0.3344	0.6454	nan	nan	nan	0.6660	0.0028	nan	nan	0.6511	0.0028

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Tokenizers 0.13.3

Task: Image Segmentation
Library: transformers
Type: segformer
License: other
Created: May 25, 2023
Updated: May 25, 2023