windowz_dce-022625

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

• Accuracy: 0.9916
• F1: 0.9914
• Iou: 0.9838
• Per Class Metrics: {0: {'f1': 0.99722, 'iou': 0.99445, 'accuracy': 0.99583}, 1: {'f1': 0.98262, 'iou': 0.96584, 'accuracy': 0.99157}, 2: {'f1': 0.752, 'iou': 0.60257, 'accuracy': 0.9957}}
• Loss: 0.0191

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
0.4609	5.0	12815	0.9814	{0: {'f1': 0.99753, 'iou': 0.99506, 'accuracy': 0.9963}, 1: {'f1': 0.97958, 'iou': 0.95998, 'accuracy': 0.99006}, 2: {'f1': 0.62099, 'iou': 0.45032, 'accuracy': 0.99369}}	0.0445
0.4462	10.0	25630	0.9830	{0: {'f1': 0.99759, 'iou': 0.99518, 'accuracy': 0.99639}, 1: {'f1': 0.98171, 'iou': 0.96408, 'accuracy': 0.99106}, 2: {'f1': 0.67311, 'iou': 0.50729, 'accuracy': 0.99467}}	0.0885
0.4105	15.0	38445	0.9847	{0: {'f1': 0.99756, 'iou': 0.99514, 'accuracy': 0.99635}, 1: {'f1': 0.98336, 'iou': 0.96726, 'accuracy': 0.99192}, 2: {'f1': 0.7548, 'iou': 0.60617, 'accuracy': 0.99557}}	0.0298
0.4006	20.0	51260	0.9834	{0: {'f1': 0.99716, 'iou': 0.99433, 'accuracy': 0.99574}, 1: {'f1': 0.98185, 'iou': 0.96435, 'accuracy': 0.99123}, 2: {'f1': 0.75043, 'iou': 0.60056, 'accuracy': 0.99546}}	0.0201
0.4016	25.0	64075	0.9838	{0: {'f1': 0.99722, 'iou': 0.99445, 'accuracy': 0.99583}, 1: {'f1': 0.98262, 'iou': 0.96584, 'accuracy': 0.99157}, 2: {'f1': 0.752, 'iou': 0.60257, 'accuracy': 0.9957}}	0.0191
0.3635	30.0	76890	0.9849	{0: {'f1': 0.99748, 'iou': 0.99496, 'accuracy': 0.99622}, 1: {'f1': 0.98326, 'iou': 0.96706, 'accuracy': 0.99192}, 2: {'f1': 0.78691, 'iou': 0.64868, 'accuracy': 0.99567}}	0.0195
0.3754	35.0	89705	0.9822	{0: {'f1': 0.99678, 'iou': 0.99359, 'accuracy': 0.99518}, 1: {'f1': 0.98001, 'iou': 0.96081, 'accuracy': 0.99042}, 2: {'f1': 0.77117, 'iou': 0.62757, 'accuracy': 0.9952}}	0.0284
0.3568	40.0	102520	0.9827	{0: {'f1': 0.99752, 'iou': 0.99506, 'accuracy': 0.99629}, 1: {'f1': 0.97971, 'iou': 0.96022, 'accuracy': 0.99027}, 2: {'f1': 0.73597, 'iou': 0.58224, 'accuracy': 0.99395}}	0.0239

Framework versions

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