segformer-b1-finetuned-segments-pv-augx3

This model is a fine-tuned version of mouadenna/segformer-b1-finetuned-segments-pv on the mouadenna/satellite_PV_dataset_train_test dataset. It achieves the following results on the evaluation set:

• Loss: 0.0157
• Mean Iou: 0.8465
• Precision: 0.9113

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: 1
• eval_batch_size: 1
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Precision
0.0038	1.0	10998	0.0083	0.8036	0.8867
0.0001	2.0	21996	0.0073	0.8363	0.8992
0.003	3.0	32994	0.0089	0.8086	0.8877
0.0044	4.0	43992	0.0098	0.8356	0.9120
0.0085	5.0	54990	0.0103	0.8363	0.8955
0.0025	6.0	65988	0.0097	0.8295	0.9055
0.0	7.0	76986	0.0135	0.8148	0.9072
0.0	8.0	87984	0.0106	0.8300	0.9011
0.0033	9.0	98982	0.0133	0.8357	0.9160
0.0022	10.0	109980	0.0128	0.8407	0.9197
0.0019	11.0	120978	0.0150	0.8455	0.9136
0.0017	12.0	131976	0.0115	0.8430	0.9191
0.0024	13.0	142974	0.0126	0.8470	0.9171
0.0029	14.0	153972	0.0155	0.8385	0.9127
0.0024	15.0	164970	0.0145	0.8430	0.9085
0.0029	16.0	175968	0.0148	0.8408	0.8980
0.0038	17.0	186966	0.0168	0.8471	0.9170
0.002	18.0	197964	0.0154	0.8437	0.9115
0.0024	19.0	208962	0.0167	0.8458	0.9276
0.0017	20.0	219960	0.0157	0.8465	0.9113

Framework versions

• Transformers 4.42.3
• Pytorch 2.1.2
• Datasets 2.20.0
• Tokenizers 0.19.1