readme: ---
  license: apache-2.0
  tags:
  - vision
  - depth-estimation
  - generated_from_trainer
  model-index:
  - name: glpn-nyu-finetuned-diode-221121-113853
    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-221121-113853
  
  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: 0.3384
  - 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
  