Model Database's logo

sayakpaul
/
glpn-nyu-finetuned-diode-221121-113853

Depth Estimation Transformers PyTorch glpn vision generated_from_trainer License: apache-2.0
Model card Files Community
Edit model card

glpn-nyu-finetuned-diode-221121-113853

This model is a fine-tuned version of vinvino02/glpn-nyu on the diode-subset dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3384
  • Mae: 0.2739
  • Rmse: 0.3959
  • Abs Rel: 0.3230
  • Log Mae: 0.1148
  • Log Rmse: 0.1651
  • Delta1: 0.5576
  • Delta2: 0.8345
  • Delta3: 0.9398

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: 1e-05
  • train_batch_size: 24
  • eval_batch_size: 48
  • seed: 2022
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Mae Rmse Abs Rel Log Mae Log Rmse Delta1 Delta2 Delta3
0.7523 1.0 72 0.5772 0.7466 0.9116 0.9709 0.2568 0.3040 0.1373 0.3324 0.6328
0.4281 2.0 144 0.3849 0.3324 0.4673 0.3934 0.1349 0.1874 0.4681 0.7753 0.9142
0.3906 3.0 216 0.3660 0.3048 0.4418 0.3593 0.1258 0.1800 0.5225 0.7997 0.9195
0.3766 4.0 288 0.3556 0.2923 0.4275 0.3383 0.1209 0.1741 0.5450 0.8157 0.9259
0.3744 5.0 360 0.3539 0.2899 0.4171 0.3435 0.1208 0.1724 0.5355 0.8173 0.9307
0.328 6.0 432 0.3498 0.2860 0.4109 0.3418 0.1196 0.1709 0.5402 0.8193 0.9334
0.3166 7.0 504 0.3451 0.2793 0.4110 0.3203 0.1166 0.1677 0.5583 0.8286 0.9331
0.2639 8.0 576 0.3475 0.2823 0.4083 0.3341 0.1182 0.1695 0.5469 0.8251 0.9337
0.2802 9.0 648 0.3422 0.2779 0.4030 0.3249 0.1163 0.1667 0.5524 0.8287 0.9366
0.2701 10.0 720 0.3411 0.2781 0.3962 0.3316 0.1168 0.1664 0.5446 0.8286 0.9396
0.2232 11.0 792 0.3408 0.2755 0.3998 0.3259 0.1154 0.1665 0.5578 0.8332 0.9383
0.2921 12.0 864 0.3391 0.2749 0.3975 0.3220 0.1152 0.1652 0.5553 0.8332 0.9390
0.2837 13.0 936 0.3400 0.2745 0.3979 0.3251 0.1150 0.1660 0.5587 0.8347 0.9386
0.2922 14.0 1008 0.3370 0.2728 0.3965 0.3184 0.1142 0.1644 0.5602 0.8359 0.9401
0.2921 15.0 1080 0.3384 0.2739 0.3959 0.3230 0.1148 0.1651 0.5576 0.8345 0.9398

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.12.1+cu116
  • Tokenizers 0.13.2
Downloads last month
0

Evaluation results

Metadata error: specify a dataset to view leaderboard