readme: ---
  license: apache-2.0
  tags:
  - vision
  - depth-estimation
  - generated_from_trainer
  model-index:
  - name: glpn-nyu-finetuned-diode-221122-082237
    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-221122-082237
  
  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: 0.3421
  - Mae: 0.2700
  - Rmse: 0.4042
  - Abs Rel: 0.3279
  - Log Mae: 0.1132
  - Log Rmse: 0.1688
  - Delta1: 0.5839
  - Delta2: 0.8408
  - Delta3: 0.9309
  
  ## 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: 2e-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: 0.2
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:-------:|:--------:|:------:|:------:|:------:|
  | 0.7577        | 1.0   | 72   | 0.5814          | 0.7579 | 0.9267 | 0.9816  | 0.2592  | 0.3062   | 0.1341 | 0.3276 | 0.6248 |
  | 0.4447        | 2.0   | 144  | 0.3947          | 0.3412 | 0.4785 | 0.4051  | 0.1381  | 0.1912   | 0.4585 | 0.7697 | 0.9072 |
  | 0.4034        | 3.0   | 216  | 0.3657          | 0.2988 | 0.4357 | 0.3629  | 0.1242  | 0.1802   | 0.5321 | 0.8054 | 0.9202 |
  | 0.3726        | 4.0   | 288  | 0.3576          | 0.2896 | 0.4176 | 0.3647  | 0.1215  | 0.1769   | 0.5376 | 0.8178 | 0.9270 |
  | 0.3656        | 5.0   | 360  | 0.3547          | 0.2818 | 0.4098 | 0.3504  | 0.1186  | 0.1732   | 0.5551 | 0.8225 | 0.9283 |
  | 0.3211        | 6.0   | 432  | 0.3495          | 0.2743 | 0.4160 | 0.3250  | 0.1155  | 0.1708   | 0.5773 | 0.8317 | 0.9258 |
  | 0.3027        | 7.0   | 504  | 0.3471          | 0.2724 | 0.4123 | 0.3226  | 0.1146  | 0.1695   | 0.5801 | 0.8345 | 0.9283 |
  | 0.2438        | 8.0   | 576  | 0.3494          | 0.2735 | 0.4097 | 0.3304  | 0.1157  | 0.1708   | 0.5741 | 0.8328 | 0.9267 |
  | 0.2512        | 9.0   | 648  | 0.3448          | 0.2700 | 0.4121 | 0.3160  | 0.1134  | 0.1683   | 0.5880 | 0.8395 | 0.9266 |
  | 0.2416        | 10.0  | 720  | 0.3439          | 0.2688 | 0.4017 | 0.3255  | 0.1135  | 0.1682   | 0.5781 | 0.8397 | 0.9324 |
  | 0.1971        | 11.0  | 792  | 0.3456          | 0.2730 | 0.4059 | 0.3348  | 0.1148  | 0.1703   | 0.5730 | 0.8370 | 0.9305 |
  | 0.2382        | 12.0  | 864  | 0.3446          | 0.2708 | 0.4069 | 0.3283  | 0.1139  | 0.1696   | 0.5818 | 0.8394 | 0.9295 |
  | 0.237         | 13.0  | 936  | 0.3417          | 0.2674 | 0.4038 | 0.3218  | 0.1123  | 0.1680   | 0.5901 | 0.8424 | 0.9307 |
  | 0.2378        | 14.0  | 1008 | 0.3421          | 0.2686 | 0.4030 | 0.3241  | 0.1130  | 0.1683   | 0.5852 | 0.8408 | 0.9311 |
  | 0.2409        | 15.0  | 1080 | 0.3421          | 0.2700 | 0.4042 | 0.3279  | 0.1132  | 0.1688   | 0.5839 | 0.8408 | 0.9309 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu116
  - Tokenizers 0.13.2
  