readme: ---
  license: apache-2.0
  tags:
  - vision
  - depth-estimation
  - generated_from_trainer
  model-index:
  - name: glpn-nyu-finetuned-diode-221230-040136
    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-221230-040136
  
  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: 0.4420
  - Mae: 0.4258
  - Rmse: 0.6168
  - Abs Rel: 0.4569
  - Log Mae: 0.1725
  - Log Rmse: 0.2275
  - Delta1: 0.3673
  - Delta2: 0.6387
  - Delta3: 0.8166
  
  ## 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: 0.0003
  - 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: 0.15
  - num_epochs: 75
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Mae    | Rmse   | Abs Rel | Log Mae | Log Rmse | Delta1 | Delta2 | Delta3 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:-------:|:--------:|:------:|:------:|:------:|
  | 1.0073        | 1.0   | 72   | 0.4928          | 0.4687 | 0.6431 | 0.5676  | 0.1955  | 0.2515   | 0.3153 | 0.5292 | 0.7843 |
  | 0.4692        | 2.0   | 144  | 0.4566          | 0.4433 | 0.6289 | 0.4690  | 0.1822  | 0.2344   | 0.3383 | 0.6035 | 0.7865 |
  | 0.4633        | 3.0   | 216  | 0.4811          | 0.4639 | 0.6338 | 0.5407  | 0.1928  | 0.2452   | 0.3191 | 0.5373 | 0.7500 |
  | 0.4369        | 4.0   | 288  | 0.4665          | 0.4449 | 0.6268 | 0.5086  | 0.1827  | 0.2387   | 0.3504 | 0.5870 | 0.7847 |
  | 0.4626        | 5.0   | 360  | 0.4516          | 0.4332 | 0.6228 | 0.4622  | 0.1759  | 0.2311   | 0.3713 | 0.6231 | 0.7962 |
  | 0.4556        | 6.0   | 432  | 0.4443          | 0.4207 | 0.6180 | 0.4486  | 0.1695  | 0.2278   | 0.3989 | 0.6454 | 0.8095 |
  | 0.4104        | 7.0   | 504  | 0.4674          | 0.4411 | 0.6250 | 0.5099  | 0.1810  | 0.2384   | 0.3602 | 0.5962 | 0.7832 |
  | 0.4035        | 8.0   | 576  | 0.4752          | 0.4547 | 0.6318 | 0.5064  | 0.1874  | 0.2396   | 0.3435 | 0.5580 | 0.7556 |
  | 0.4215        | 9.0   | 648  | 0.4879          | 0.4711 | 0.6411 | 0.5626  | 0.1958  | 0.2496   | 0.3184 | 0.5331 | 0.7103 |
  | 0.404         | 10.0  | 720  | 0.4715          | 0.4479 | 0.6276 | 0.5254  | 0.1841  | 0.2406   | 0.3463 | 0.5859 | 0.7681 |
  | 0.3788        | 11.0  | 792  | 0.4607          | 0.4487 | 0.6248 | 0.4814  | 0.1835  | 0.2324   | 0.3458 | 0.5698 | 0.7540 |
  | 0.4399        | 12.0  | 864  | 0.4925          | 0.4609 | 0.6363 | 0.5713  | 0.1910  | 0.2499   | 0.3317 | 0.5621 | 0.7471 |
  | 0.4287        | 13.0  | 936  | 0.4784          | 0.4463 | 0.6321 | 0.5211  | 0.1836  | 0.2430   | 0.3581 | 0.5865 | 0.7841 |
  | 0.4079        | 14.0  | 1008 | 0.4664          | 0.4514 | 0.6289 | 0.4921  | 0.1848  | 0.2360   | 0.3463 | 0.5705 | 0.7463 |
  | 0.4246        | 15.0  | 1080 | 0.4734          | 0.4548 | 0.6318 | 0.5166  | 0.1872  | 0.2410   | 0.3355 | 0.5666 | 0.7618 |
  | 0.4015        | 16.0  | 1152 | 0.4874          | 0.4581 | 0.6324 | 0.5738  | 0.1894  | 0.2484   | 0.3354 | 0.5611 | 0.7531 |
  | 0.3769        | 17.0  | 1224 | 0.4927          | 0.4622 | 0.6341 | 0.5808  | 0.1911  | 0.2497   | 0.3326 | 0.5531 | 0.7436 |
  | 0.4393        | 18.0  | 1296 | 0.4903          | 0.4666 | 0.6355 | 0.5729  | 0.1937  | 0.2496   | 0.3235 | 0.5415 | 0.7276 |
  | 0.3765        | 19.0  | 1368 | 0.4808          | 0.4568 | 0.6311 | 0.5585  | 0.1889  | 0.2460   | 0.3319 | 0.5596 | 0.7620 |
  | 0.394         | 20.0  | 1440 | 0.4363          | 0.4262 | 0.6366 | 0.4018  | 0.1718  | 0.2302   | 0.4056 | 0.6590 | 0.7972 |
  | 0.374         | 21.0  | 1512 | 0.4500          | 0.4262 | 0.6286 | 0.4592  | 0.1726  | 0.2339   | 0.3895 | 0.6529 | 0.8082 |
  | 0.3511        | 22.0  | 1584 | 0.4436          | 0.4316 | 0.6251 | 0.4535  | 0.1757  | 0.2300   | 0.3593 | 0.6330 | 0.8068 |
  | 0.3999        | 23.0  | 1656 | 0.4715          | 0.4493 | 0.6285 | 0.5333  | 0.1847  | 0.2414   | 0.3363 | 0.5844 | 0.7834 |
  | 0.4154        | 24.0  | 1728 | 0.4659          | 0.4415 | 0.6248 | 0.5114  | 0.1807  | 0.2379   | 0.3510 | 0.5953 | 0.7975 |
  | 0.3788        | 25.0  | 1800 | 0.4463          | 0.4292 | 0.6274 | 0.4328  | 0.1735  | 0.2298   | 0.3851 | 0.6403 | 0.7899 |
  | 0.3676        | 26.0  | 1872 | 0.4444          | 0.4233 | 0.6160 | 0.4481  | 0.1707  | 0.2264   | 0.3900 | 0.6411 | 0.7991 |
  | 0.3538        | 27.0  | 1944 | 0.4533          | 0.4435 | 0.6234 | 0.4714  | 0.1817  | 0.2311   | 0.3387 | 0.5813 | 0.7915 |
  | 0.3678        | 28.0  | 2016 |