readme: ---
  license: apache-2.0
  tags:
  - vision
  - depth-estimation
  - generated_from_trainer
  model-index:
  - name: glpn-kitti-finetuned-diode-221214-123047
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # glpn-kitti-finetuned-diode-221214-123047
  
  This model is a fine-tuned version of [vinvino02/glpn-kitti](https://huggingface.co/vinvino02/glpn-kitti) on the diode-subset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3497
  - Mae: 0.2847
  - Rmse: 0.3977
  - Abs Rel: 0.3477
  - Log Mae: 0.1203
  - Log Rmse: 0.1726
  - Delta1: 0.5217
  - Delta2: 0.8246
  - Delta3: 0.9436
  
  ## 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: 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: 0.15
  - num_epochs: 25
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Mae    | Rmse   | Abs Rel | Log Mae | Log Rmse | Delta1 | Delta2 | Delta3 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:-------:|:--------:|:------:|:------:|:------:|
  | 0.6103        | 1.0   | 72   | 0.4449          | 0.3914 | 0.5513 | 0.4625  | 0.1615  | 0.2186   | 0.3918 | 0.6910 | 0.8549 |
  | 0.3762        | 2.0   | 144  | 0.4095          | 0.3583 | 0.4876 | 0.4281  | 0.1505  | 0.2015   | 0.4065 | 0.7121 | 0.8901 |
  | 0.341         | 3.0   | 216  | 0.3768          | 0.3046 | 0.4061 | 0.4016  | 0.1313  | 0.1840   | 0.4757 | 0.7938 | 0.9309 |
  | 0.291         | 4.0   | 288  | 0.3853          | 0.3227 | 0.4495 | 0.3724  | 0.1360  | 0.1869   | 0.4646 | 0.7680 | 0.9127 |
  | 0.2861        | 5.0   | 360  | 0.3786          | 0.3151 | 0.4257 | 0.4065  | 0.1344  | 0.1876   | 0.4597 | 0.7785 | 0.9329 |
  | 0.2539        | 6.0   | 432  | 0.3687          | 0.3158 | 0.4546 | 0.3329  | 0.1316  | 0.1821   | 0.4732 | 0.7869 | 0.9138 |
  | 0.2199        | 7.0   | 504  | 0.3705          | 0.3122 | 0.4479 | 0.3378  | 0.1312  | 0.1820   | 0.4784 | 0.7888 | 0.9189 |
  | 0.1728        | 8.0   | 576  | 0.3578          | 0.2895 | 0.4008 | 0.3675  | 0.1235  | 0.1766   | 0.5101 | 0.8178 | 0.9420 |
  | 0.1877        | 9.0   | 648  | 0.3589          | 0.2846 | 0.3846 | 0.3721  | 0.1235  | 0.1764   | 0.5144 | 0.8170 | 0.9403 |
  | 0.1541        | 10.0  | 720  | 0.3521          | 0.2831 | 0.3997 | 0.3283  | 0.1201  | 0.1712   | 0.5241 | 0.8260 | 0.9422 |
  | 0.1414        | 11.0  | 792  | 0.3460          | 0.2735 | 0.3772 | 0.3419  | 0.1173  | 0.1691   | 0.5409 | 0.8360 | 0.9469 |
  | 0.1643        | 12.0  | 864  | 0.3530          | 0.2878 | 0.4100 | 0.3313  | 0.1214  | 0.1736   | 0.5249 | 0.8214 | 0.9344 |
  | 0.1724        | 13.0  | 936  | 0.3606          | 0.2995 | 0.4249 | 0.3459  | 0.1255  | 0.1775   | 0.5057 | 0.8069 | 0.9323 |
  | 0.1514        | 14.0  | 1008 | 0.3477          | 0.2832 | 0.3881 | 0.3596  | 0.1206  | 0.1726   | 0.5174 | 0.8253 | 0.9437 |
  | 0.1535        | 15.0  | 1080 | 0.3535          | 0.2961 | 0.4242 | 0.3412  | 0.1231  | 0.1753   | 0.5186 | 0.8080 | 0.9332 |
  | 0.1233        | 16.0  | 1152 | 0.3508          | 0.2896 | 0.4104 | 0.3391  | 0.1213  | 0.1727   | 0.5225 | 0.8165 | 0.9398 |
  | 0.116         | 17.0  | 1224 | 0.3519          | 0.2874 | 0.3989 | 0.3533  | 0.1215  | 0.1731   | 0.5200 | 0.8179 | 0.9407 |
  | 0.1532        | 18.0  | 1296 | 0.3532          | 0.2965 | 0.4200 | 0.3459  | 0.1236  | 0.1747   | 0.5147 | 0.8035 | 0.9353 |
  | 0.1179        | 19.0  | 1368 | 0.3497          | 0.2828 | 0.3896 | 0.3557  | 0.1204  | 0.1728   | 0.5200 | 0.8260 | 0.9457 |
  | 0.1326        | 20.0  | 1440 | 0.3467          | 0.2787 | 0.3848 | 0.3475  | 0.1185  | 0.1704   | 0.5257 | 0.8330 | 0.9479 |
  | 0.1069        | 21.0  | 1512 | 0.3471          | 0.2807 | 0.3922 | 0.3418  | 0.1187  | 0.1707   | 0.5288 | 0.8297 | 0.9452 |
  | 0.1049        | 22.0  | 1584 | 0.3474          | 0.2864 | 0.4048 | 0.3387  | 0.1199  | 0.1717   | 0.5227 | 0.8251 | 0.9428 |
  | 0.103         | 23.0  | 1656 | 0.3483          | 0.2840 | 0.3991 | 0.3416  | 0.1196  | 0.1717   | 0.5254 | 0.8269 | 0.9431 |
  | 0.1184        | 24.0  | 1728 | 0.3473          | 0.2839 | 0.3960 | 0.3450  | 0.1198  | 0.1717   | 0.5223 | 0.8251 | 0.9443 |
  | 0.1258        | 25.0  | 1800 | 0.3497          | 0.2847 | 0.3977 | 0.3477  | 0.1203  | 0.1726   | 0.5217 | 0.8246 | 0.9436 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu116
  - Tokenizers 0.13.2
  