readme: ---
  license: apache-2.0
  tags:
  - vision
  - depth-estimation
  - generated_from_trainer
  model-index:
  - name: glpn-nyu-finetuned-diode-221121-063504
    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-221121-063504
  
  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: 0.3533
  - Mae: 0.2668
  - Rmse: 0.3716
  - Abs Rel: 0.3427
  - Log Mae: 0.1167
  - Log Rmse: 0.1703
  - Delta1: 0.5522
  - Delta2: 0.8362
  - Delta3: 0.9382
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:-------:|:--------:|:------:|:------:|:------:|
  | 1.3991        | 1.0   | 72   | 1.2199          | 3.6023 | 3.6519 | 5.2780  | 0.7010  | 0.7461   | 0.0    | 0.0007 | 0.0616 |
  | 1.1099        | 2.0   | 144  | 0.7471          | 1.2562 | 1.5028 | 1.6644  | 0.3550  | 0.4165   | 0.0965 | 0.2342 | 0.4292 |
  | 0.5036        | 3.0   | 216  | 0.4876          | 0.5019 | 0.6198 | 0.7615  | 0.2000  | 0.2599   | 0.2878 | 0.5643 | 0.7803 |
  | 0.4157        | 4.0   | 288  | 0.3789          | 0.3008 | 0.4211 | 0.3793  | 0.1291  | 0.1840   | 0.4961 | 0.7961 | 0.9261 |
  | 0.4043        | 5.0   | 360  | 0.3795          | 0.3025 | 0.4117 | 0.4028  | 0.1303  | 0.1850   | 0.4889 | 0.7892 | 0.9278 |
  | 0.3638        | 6.0   | 432  | 0.3790          | 0.3022 | 0.4019 | 0.4175  | 0.1313  | 0.1862   | 0.4851 | 0.7889 | 0.9262 |
  | 0.3532        | 7.0   | 504  | 0.3605          | 0.2756 | 0.3864 | 0.3447  | 0.1201  | 0.1732   | 0.5397 | 0.8202 | 0.9330 |
  | 0.3087        | 8.0   | 576  | 0.3599          | 0.2781 | 0.3896 | 0.3365  | 0.1206  | 0.1722   | 0.5312 | 0.8183 | 0.9332 |
  | 0.3232        | 9.0   | 648  | 0.3613          | 0.2772 | 0.3879 | 0.3444  | 0.1204  | 0.1733   | 0.5341 | 0.8237 | 0.9334 |
  | 0.3072        | 10.0  | 720  | 0.3570          | 0.2752 | 0.3794 | 0.3582  | 0.1195  | 0.1731   | 0.5341 | 0.8270 | 0.9374 |
  | 0.2673        | 11.0  | 792  | 0.3633          | 0.2747 | 0.3838 | 0.3390  | 0.1207  | 0.1728   | 0.5330 | 0.8221 | 0.9333 |
  | 0.3222        | 12.0  | 864  | 0.3548          | 0.2713 | 0.3783 | 0.3441  | 0.1180  | 0.1711   | 0.5448 | 0.8315 | 0.9367 |
  | 0.3072        | 13.0  | 936  | 0.3532          | 0.2668 | 0.3700 | 0.3441  | 0.1168  | 0.1701   | 0.5502 | 0.8353 | 0.9387 |
  | 0.3214        | 14.0  | 1008 | 0.3553          | 0.2674 | 0.3747 | 0.3322  | 0.1177  | 0.1701   | 0.5472 | 0.8324 | 0.9355 |
  | 0.3406        | 15.0  | 1080 | 0.3533          | 0.2668 | 0.3716 | 0.3427  | 0.1167  | 0.1703   | 0.5522 | 0.8362 | 0.9382 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu116
  - Tokenizers 0.13.2
  