readme: ---
  license: apache-2.0
  tags:
  - vision
  - depth-estimation
  - generated_from_trainer
  model-index:
  - name: glpn-nyu-finetuned-diode-221122-014502
    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-221122-014502
  
  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: 0.3476
  - Mae: 0.2763
  - Rmse: 0.4088
  - Abs Rel: 0.3308
  - Log Mae: 0.1161
  - Log Rmse: 0.1700
  - Delta1: 0.5682
  - Delta2: 0.8301
  - Delta3: 0.9279
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:-------:|:--------:|:------:|:------:|:------:|
  | 0.7598        | 1.0   | 72   | 0.5809          | 0.7606 | 0.9281 | 0.9834  | 0.2597  | 0.3064   | 0.1320 | 0.3250 | 0.6234 |
  | 0.4481        | 2.0   | 144  | 0.4013          | 0.3507 | 0.4879 | 0.4181  | 0.1415  | 0.1950   | 0.4427 | 0.7602 | 0.9021 |
  | 0.4066        | 3.0   | 216  | 0.3706          | 0.3081 | 0.4484 | 0.3675  | 0.1269  | 0.1823   | 0.5187 | 0.7977 | 0.9148 |
  | 0.3965        | 4.0   | 288  | 0.3641          | 0.2987 | 0.4336 | 0.3607  | 0.1239  | 0.1787   | 0.5294 | 0.8072 | 0.9205 |
  | 0.3942        | 5.0   | 360  | 0.3582          | 0.2903 | 0.4251 | 0.3490  | 0.1207  | 0.1753   | 0.5466 | 0.8165 | 0.9232 |
  | 0.3575        | 6.0   | 432  | 0.3568          | 0.2898 | 0.4184 | 0.3569  | 0.1211  | 0.1753   | 0.5390 | 0.8171 | 0.9265 |
  | 0.3418        | 7.0   | 504  | 0.3490          | 0.2771 | 0.4178 | 0.3248  | 0.1156  | 0.1707   | 0.5783 | 0.8312 | 0.9259 |
  | 0.2916        | 8.0   | 576  | 0.3512          | 0.2819 | 0.4172 | 0.3373  | 0.1178  | 0.1725   | 0.5620 | 0.8253 | 0.9262 |
  | 0.3055        | 9.0   | 648  | 0.3506          | 0.2808 | 0.4091 | 0.3422  | 0.1180  | 0.1718   | 0.5537 | 0.8248 | 0.9292 |
  | 0.2932        | 10.0  | 720  | 0.3518          | 0.2809 | 0.4110 | 0.3441  | 0.1182  | 0.1724   | 0.5548 | 0.8239 | 0.9290 |
  | 0.2518        | 11.0  | 792  | 0.3476          | 0.2756 | 0.4115 | 0.3265  | 0.1155  | 0.1700   | 0.5741 | 0.8326 | 0.9264 |
  | 0.3177        | 12.0  | 864  | 0.3491          | 0.2784 | 0.4104 | 0.3333  | 0.1169  | 0.1706   | 0.5620 | 0.8290 | 0.9283 |
  | 0.3038        | 13.0  | 936  | 0.3503          | 0.2795 | 0.4094 | 0.3410  | 0.1175  | 0.1717   | 0.5596 | 0.8275 | 0.9283 |
  | 0.3299        | 14.0  | 1008 | 0.3460          | 0.2750 | 0.4098 | 0.3257  | 0.1154  | 0.1693   | 0.5721 | 0.8325 | 0.9283 |
  | 0.3325        | 15.0  | 1080 | 0.3476          | 0.2763 | 0.4088 | 0.3308  | 0.1161  | 0.1700   | 0.5682 | 0.8301 | 0.9279 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu116
  - Tokenizers 0.13.2
  