readme: ---
  license: apache-2.0
  tags:
  - vision
  - depth-estimation
  - generated_from_trainer
  model-index:
  - name: glpn-nyu-finetuned-diode-221214-054706
    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-221214-054706
  
  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: 0.3340
  - Mae: 0.2649
  - Rmse: 0.3917
  - Abs Rel: 0.3138
  - Log Mae: 0.1111
  - Log Rmse: 0.1640
  - Delta1: 0.5843
  - Delta2: 0.8459
  - Delta3: 0.9413
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:-------:|:--------:|:------:|:------:|:------:|
  | 0.746         | 1.0   | 72   | 0.5730          | 0.7316 | 0.8964 | 0.9501  | 0.2530  | 0.3005   | 0.1427 | 0.3446 | 0.6453 |
  | 0.4215        | 2.0   | 144  | 0.3764          | 0.3140 | 0.4548 | 0.3607  | 0.1286  | 0.1819   | 0.5054 | 0.7927 | 0.9161 |
  | 0.3566        | 3.0   | 216  | 0.3568          | 0.2894 | 0.4226 | 0.3436  | 0.1206  | 0.1751   | 0.5475 | 0.8178 | 0.9257 |
  | 0.322         | 4.0   | 288  | 0.3523          | 0.2818 | 0.4069 | 0.3541  | 0.1188  | 0.1740   | 0.5508 | 0.8219 | 0.9325 |
  | 0.3066        | 5.0   | 360  | 0.3464          | 0.2777 | 0.4090 | 0.3283  | 0.1164  | 0.1695   | 0.5609 | 0.8328 | 0.9313 |
  | 0.256         | 6.0   | 432  | 0.3384          | 0.2687 | 0.3927 | 0.3173  | 0.1136  | 0.1647   | 0.5665 | 0.8381 | 0.9394 |
  | 0.2268        | 7.0   | 504  | 0.3407          | 0.2747 | 0.4138 | 0.3091  | 0.1143  | 0.1672   | 0.5716 | 0.8380 | 0.9322 |
  | 0.1721        | 8.0   | 576  | 0.3346          | 0.2631 | 0.3850 | 0.3176  | 0.1108  | 0.1636   | 0.5804 | 0.8489 | 0.9452 |
  | 0.1898        | 9.0   | 648  | 0.3362          | 0.2656 | 0.3994 | 0.3100  | 0.1112  | 0.1650   | 0.5910 | 0.8455 | 0.9368 |
  | 0.1609        | 10.0  | 720  | 0.3355          | 0.2667 | 0.3866 | 0.3242  | 0.1124  | 0.1648   | 0.5693 | 0.8452 | 0.9433 |
  | 0.139         | 11.0  | 792  | 0.3344          | 0.2660 | 0.3954 | 0.3115  | 0.1112  | 0.1639   | 0.5833 | 0.8453 | 0.9409 |
  | 0.1772        | 12.0  | 864  | 0.3360          | 0.2667 | 0.3979 | 0.3137  | 0.1115  | 0.1650   | 0.5854 | 0.8449 | 0.9393 |
  | 0.1631        | 13.0  | 936  | 0.3353          | 0.2652 | 0.3938 | 0.3134  | 0.1112  | 0.1645   | 0.5858 | 0.8451 | 0.9403 |
  | 0.1736        | 14.0  | 1008 | 0.3367          | 0.2663 | 0.3954 | 0.3163  | 0.1117  | 0.1653   | 0.5840 | 0.8446 | 0.9391 |
  | 0.1736        | 15.0  | 1080 | 0.3340          | 0.2649 | 0.3917 | 0.3138  | 0.1111  | 0.1640   | 0.5843 | 0.8459 | 0.9413 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu116
  - Tokenizers 0.13.2
  