mit-b0-building-damage-lora

ibrahim-601/mit-b0-building-damage-lora

mit-b0-building-damage-lora is a machine learning model from ibrahim-601. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as other.

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

Downloads · 30 days

Access

Public

Updated Nov 13, 2023

Repo size

192 MB

Likes

Public

Hugging Face

Repo makeup

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.bin2.1 MB · 100%

At a glance

License: other
Access: Public
Created: Nov 4, 2023
Updated: Nov 13, 2023
SHA: dd197121

Base models

nvidia/mit-b0

Model card

From the Hugging Face model README

mit-b0-building-damage-lora

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

Loss: 0.0661
Mean Iou: 0.3623
Mean Accuracy: 0.7245
Overall Accuracy: 0.7245
Accuracy Building: 0.7245
Iou Building: 0.7245

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: 0.0005
train_batch_size: 8
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Building	Iou Building
0.0618	1.0	700	0.1463	0.4063	0.8125	0.8125	0.8125	0.8125
0.0813	2.0	1400	0.0861	0.3950	0.7900	0.7900	0.7900	0.7900
0.0715	3.0	2100	0.0856	0.3844	0.7689	0.7689	0.7689	0.7689
0.076	4.0	2800	0.1296	0.4161	0.8322	0.8322	0.8322	0.8322
0.0587	5.0	3500	0.0702	0.3078	0.6156	0.6156	0.6156	0.6156
0.0662	6.0	4200	0.0708	0.3613	0.7226	0.7226	0.7226	0.7226
0.059	7.0	4900	0.1063	0.4125	0.8249	0.8249	0.8249	0.8249
0.0532	8.0	5600	0.0693	0.3547	0.7094	0.7094	0.7094	0.7094
0.066	9.0	6300	0.0754	0.3932	0.7863	0.7863	0.7863	0.7863
0.0628	10.0	7000	0.0692	0.3874	0.7747	0.7747	0.7747	0.7747
0.0805	11.0	7700	0.0701	0.3896	0.7793	0.7793	0.7793	0.7793
0.0595	12.0	8400	0.0663	0.3774	0.7549	0.7549	0.7549	0.7549
0.0705	13.0	9100	0.0653	0.3717	0.7433	0.7433	0.7433	0.7433
0.071	14.0	9800	0.0651	0.3731	0.7461	0.7461	0.7461	0.7461
0.0656	15.0	10500	0.0648	0.3613	0.7227	0.7227	0.7227	0.7227

Framework versions

Transformers 4.33.0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3

License: other
Created: Nov 4, 2023
Updated: Nov 13, 2023