windowz_test-022625

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

• Accuracy: 0.9908
• F1: 0.9910
• Iou: 0.9832
• Per Class Metrics: {0: {'f1': 0.99751, 'iou': 0.99504, 'accuracy': 0.99628}, 1: {'f1': 0.98091, 'iou': 0.96254, 'accuracy': 0.99081}, 2: {'f1': 0.73081, 'iou': 0.5758, 'accuracy': 0.99448}}
• Loss: 0.0169

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 1000
• num_epochs: 100

Training results

Training Loss	Epoch	Step		Class Metrics	Validation Loss
0.4586	5.0	12815	0.9710	{0: {'f1': 0.99385, 'iou': 0.98778, 'accuracy': 0.99081}, 1: {'f1': 0.96879, 'iou': 0.93947, 'accuracy': 0.98478}, 2: {'f1': 0.62073, 'iou': 0.45004, 'accuracy': 0.99365}}	0.0890
0.4363	10.0	25630	0.9810	{0: {'f1': 0.99729, 'iou': 0.9946, 'accuracy': 0.99595}, 1: {'f1': 0.97943, 'iou': 0.95969, 'accuracy': 0.99}, 2: {'f1': 0.6238, 'iou': 0.45327, 'accuracy': 0.99404}}	0.0220
0.4148	15.0	38445	0.9785	{0: {'f1': 0.99619, 'iou': 0.9924, 'accuracy': 0.99428}, 1: {'f1': 0.97538, 'iou': 0.95195, 'accuracy': 0.98824}, 2: {'f1': 0.71793, 'iou': 0.55998, 'accuracy': 0.99388}}	0.0593
0.3935	20.0	51260	0.9743	{0: {'f1': 0.99419, 'iou': 0.98845, 'accuracy': 0.99126}, 1: {'f1': 0.97367, 'iou': 0.94869, 'accuracy': 0.9874}, 2: {'f1': 0.67815, 'iou': 0.51303, 'accuracy': 0.99437}}	0.0229
0.3755	25.0	64075	0.9826	{0: {'f1': 0.99767, 'iou': 0.99534, 'accuracy': 0.99651}, 1: {'f1': 0.9796, 'iou': 0.96001, 'accuracy': 0.9902}, 2: {'f1': 0.71337, 'iou': 0.55445, 'accuracy': 0.99367}}	0.0187
0.3834	30.0	76890	0.9814	{0: {'f1': 0.99714, 'iou': 0.9943, 'accuracy': 0.99572}, 1: {'f1': 0.97847, 'iou': 0.95784, 'accuracy': 0.98967}, 2: {'f1': 0.71791, 'iou': 0.55995, 'accuracy': 0.99391}}	0.0175
0.3609	35.0	89705	0.9832	{0: {'f1': 0.99751, 'iou': 0.99504, 'accuracy': 0.99628}, 1: {'f1': 0.98091, 'iou': 0.96254, 'accuracy': 0.99081}, 2: {'f1': 0.73081, 'iou': 0.5758, 'accuracy': 0.99448}}	0.0169
0.364	40.0	102520	0.9815	{0: {'f1': 0.99756, 'iou': 0.99513, 'accuracy': 0.99635}, 1: {'f1': 0.97769, 'iou': 0.95635, 'accuracy': 0.98933}, 2: {'f1': 0.70736, 'iou': 0.54722, 'accuracy': 0.99295}}	0.0210
0.3561	45.0	115335	0.9857	{0: {'f1': 0.99789, 'iou': 0.9958, 'accuracy': 0.99685}, 1: {'f1': 0.98385, 'iou': 0.96822, 'accuracy': 0.99221}, 2: {'f1': 0.77212, 'iou': 0.62883, 'accuracy': 0.99536}}	0.0208
0.3714	50.0	128150	0.9843	{0: {'f1': 0.99769, 'iou': 0.99539, 'accuracy': 0.99654}, 1: {'f1': 0.98205, 'iou': 0.96473, 'accuracy': 0.99135}, 2: {'f1': 0.75937, 'iou': 0.61209, 'accuracy': 0.99479}}	0.0170

Framework versions

• Transformers 4.45.0
• Pytorch 2.5.1+cu124
• Datasets 2.21.0
• Tokenizers 0.20.3