segformer-b0-scene-parse-150

This model is a fine-tuned version of nvidia/mit-b0 on the scene_parse_150 dataset. It achieves the following results on the evaluation set:

• eval_loss: 3.4741
• eval_mean_iou: 0.0469
• eval_mean_accuracy: 0.0897
• eval_overall_accuracy: 0.4191
• eval_per_category_iou: [0.2665166173083251, 0.4167168366238619, 0.8361890939548855, 0.33169163825937054, 0.3642621950031498, 0.07457156680502151, 0.38010872244357347, 0.0, 0.028505594009054825, 0.0, 0.08140381534876948, 0.0, 0.0, 0.0, nan, 0.002712308267863823, 0.21742988456929635, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0]
• eval_per_category_accuracy: [0.7619990215632408, 0.5866148267878205, 0.9802105067142923, 0.7539035299949252, 0.7073735188957063, 0.0895565749235474, 0.924393826615639, nan, 0.029600897280119637, 0.0, 0.09706546275395034, 0.0, 0.0, 0.0, nan, 0.002747513027001421, 0.3571304001195874, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0]
• eval_runtime: 14.2264
• eval_samples_per_second: 0.703
• eval_steps_per_second: 0.351
• epoch: 4.0
• step: 80

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

Framework versions

• Transformers 4.38.1
• Pytorch 2.1.0+cu121
• Datasets 2.17.1
• Tokenizers 0.15.2