readme: ---
  license: apache-2.0
  tags:
  - vision
  - depth-estimation
  - generated_from_trainer
  model-index:
  - name: glpn-nyu-finetuned-diode-221214-081122
    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-nyu-finetuned-diode-221214-081122
  
  This model is a fine-tuned version of [vinvino02/glpn-nyu](https://huggingface.co/vinvino02/glpn-nyu) on the diode-subset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3242
  - Mae: 0.2603
  - Rmse: 0.3997
  - Abs Rel: 0.3010
  - Log Mae: 0.1073
  - Log Rmse: 0.1624
  - Delta1: 0.6187
  - Delta2: 0.8455
  - Delta3: 0.9378
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:-------:|:--------:|:------:|:------:|:------:|
  | 0.6896        | 1.0   | 72   | 0.4753          | 0.4670 | 0.6226 | 0.5658  | 0.1791  | 0.2313   | 0.2950 | 0.6310 | 0.8562 |
  | 0.3628        | 2.0   | 144  | 0.3565          | 0.2956 | 0.4307 | 0.3421  | 0.1226  | 0.1737   | 0.5285 | 0.8079 | 0.9245 |
  | 0.3168        | 3.0   | 216  | 0.3486          | 0.2774 | 0.3963 | 0.3464  | 0.1172  | 0.1710   | 0.5561 | 0.8285 | 0.9358 |
  | 0.2734        | 4.0   | 288  | 0.3368          | 0.2669 | 0.3962 | 0.3260  | 0.1122  | 0.1671   | 0.5787 | 0.8453 | 0.9383 |
  | 0.2678        | 5.0   | 360  | 0.3419          | 0.2700 | 0.4136 | 0.3118  | 0.1130  | 0.1689   | 0.5869 | 0.8399 | 0.9289 |
  | 0.2271        | 6.0   | 432  | 0.3270          | 0.2611 | 0.3890 | 0.3050  | 0.1091  | 0.1608   | 0.5899 | 0.8500 | 0.9453 |
  | 0.1905        | 7.0   | 504  | 0.3331          | 0.2651 | 0.3996 | 0.3086  | 0.1110  | 0.1645   | 0.5925 | 0.8391 | 0.9405 |
  | 0.1436        | 8.0   | 576  | 0.3323          | 0.2648 | 0.4039 | 0.3087  | 0.1097  | 0.1653   | 0.6019 | 0.8475 | 0.9345 |
  | 0.1687        | 9.0   | 648  | 0.3274          | 0.2620 | 0.3887 | 0.3129  | 0.1092  | 0.1622   | 0.5954 | 0.8464 | 0.9422 |
  | 0.1407        | 10.0  | 720  | 0.3344          | 0.2689 | 0.4134 | 0.3079  | 0.1107  | 0.1667   | 0.6039 | 0.8423 | 0.9287 |
  | 0.1159        | 11.0  | 792  | 0.3302          | 0.2675 | 0.4081 | 0.3032  | 0.1103  | 0.1646   | 0.6035 | 0.8406 | 0.9334 |
  | 0.16          | 12.0  | 864  | 0.3262          | 0.2599 | 0.3989 | 0.2986  | 0.1074  | 0.1621   | 0.6177 | 0.8460 | 0.9371 |
  | 0.1385        | 13.0  | 936  | 0.3287          | 0.2616 | 0.3976 | 0.3114  | 0.1085  | 0.1643   | 0.6095 | 0.8472 | 0.9363 |
  | 0.156         | 14.0  | 1008 | 0.3291          | 0.2690 | 0.4147 | 0.3048  | 0.1101  | 0.1654   | 0.6082 | 0.8390 | 0.9305 |
  | 0.1534        | 15.0  | 1080 | 0.3267          | 0.2651 | 0.3994 | 0.3084  | 0.1096  | 0.1632   | 0.6030 | 0.8406 | 0.9376 |
  | 0.1196        | 16.0  | 1152 | 0.3248          | 0.2588 | 0.4028 | 0.2908  | 0.1065  | 0.1615   | 0.6265 | 0.8467 | 0.9357 |
  | 0.0983        | 17.0  | 1224 | 0.3249          | 0.2612 | 0.4046 | 0.2940  | 0.1075  | 0.1620   | 0.6198 | 0.8440 | 0.9346 |
  | 0.1347        | 18.0  | 1296 | 0.3209          | 0.2608 | 0.4012 | 0.2971  | 0.1069  | 0.1614   | 0.6201 | 0.8473 | 0.9376 |
  | 0.107         | 19.0  | 1368 | 0.3249          | 0.2624 | 0.4026 | 0.3013  | 0.1079  | 0.1628   | 0.6149 | 0.8453 | 0.9362 |
  | 0.1214        | 20.0  | 1440 | 0.3213          | 0.2586 | 0.3976 | 0.2962  | 0.1065  | 0.1609   | 0.6219 | 0.8464 | 0.9382 |
  | 0.0921        | 21.0  | 1512 | 0.3240          | 0.2600 | 0.3971 | 0.3028  | 0.1074  | 0.1624   | 0.6179 | 0.8457 | 0.9383 |
  | 0.0906        | 22.0  | 1584 | 0.3239          | 0.2602 | 0.4025 | 0.2968  | 0.1069  | 0.1622   | 0.6227 | 0.8461 | 0.9365 |
  | 0.0978        | 23.0  | 1656 | 0.3230          | 0.2588 | 0.3990 | 0.2969  | 0.1066  | 0.1617   | 0.6234 | 0.8462 | 0.9371 |
  | 0.1377        | 24.0  | 1728 | 0.3244          | 0.2612 | 0.4013 | 0.3005  | 0.1076  | 0.1626   | 0.6180 | 0.8447 | 0.9359 |
  | 0.1253        | 25.0  | 1800 | 0.3242          | 0.2603 | 0.3997 | 0.3010  | 0.1073  | 0.1624   | 0.6187 | 0.8455 | 0.9378 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu116
  - Tokenizers 0.13.2
  