readme: ---
  license: apache-2.0
  tags:
  - vision
  - depth-estimation
  - generated_from_trainer
  model-index:
  - name: glpn-nyu-finetuned-diode-230131-041708
    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-230131-041708
  
  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: 0.4425
  - Mae: 0.4270
  - Rmse: 0.6196
  - Abs Rel: 0.4543
  - Log Mae: 0.1732
  - Log Rmse: 0.2288
  - Delta1: 0.3787
  - Delta2: 0.6298
  - Delta3: 0.8083
  
  ## 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
  - num_epochs: 100
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Mae    | Rmse   | Abs Rel | Log Mae | Log Rmse | Delta1 | Delta2 | Delta3 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:-------:|:--------:|:------:|:------:|:------:|
  | 0.5276        | 1.0   | 72   | 0.4701          | 0.4590 | 0.6348 | 0.4983  | 0.1903  | 0.2393   | 0.3169 | 0.5544 | 0.7661 |
  | 0.4595        | 2.0   | 144  | 0.4867          | 0.4690 | 0.6369 | 0.5588  | 0.1956  | 0.2483   | 0.3090 | 0.5269 | 0.7532 |
  | 0.4802        | 3.0   | 216  | 0.4854          | 0.4648 | 0.6344 | 0.5581  | 0.1935  | 0.2475   | 0.3135 | 0.5355 | 0.7531 |
  | 0.4566        | 4.0   | 288  | 0.4709          | 0.4559 | 0.6756 | 0.4223  | 0.1890  | 0.2516   | 0.3668 | 0.6329 | 0.7696 |
  | 0.4916        | 5.0   | 360  | 0.4835          | 0.4555 | 0.6343 | 0.5302  | 0.1881  | 0.2447   | 0.3435 | 0.5716 | 0.7437 |
  | 0.4822        | 6.0   | 432  | 0.4756          | 0.4585 | 0.6301 | 0.5264  | 0.1894  | 0.2414   | 0.3238 | 0.5628 | 0.7435 |
  | 0.4588        | 7.0   | 504  | 0.4655          | 0.4481 | 0.6509 | 0.4425  | 0.1843  | 0.2413   | 0.3498 | 0.6157 | 0.7809 |
  | 0.4214        | 8.0   | 576  | 0.4869          | 0.4706 | 0.6391 | 0.5669  | 0.1961  | 0.2500   | 0.3033 | 0.5388 | 0.7371 |
  | 0.426         | 9.0   | 648  | 0.4835          | 0.4679 | 0.6472 | 0.5117  | 0.1951  | 0.2486   | 0.3216 | 0.5474 | 0.7399 |
  | 0.4135        | 10.0  | 720  | 0.4621          | 0.4439 | 0.6287 | 0.4803  | 0.1825  | 0.2365   | 0.3451 | 0.5887 | 0.7878 |
  | 0.3778        | 11.0  | 792  | 0.4756          | 0.4566 | 0.6337 | 0.5174  | 0.1892  | 0.2431   | 0.3297 | 0.5560 | 0.7690 |
  | 0.426         | 12.0  | 864  | 0.4542          | 0.4362 | 0.6219 | 0.4621  | 0.1779  | 0.2303   | 0.3572 | 0.6083 | 0.7835 |
  | 0.4282        | 13.0  | 936  | 0.4514          | 0.4306 | 0.6195 | 0.4678  | 0.1754  | 0.2307   | 0.3661 | 0.6228 | 0.8083 |
  | 0.4045        | 14.0  | 1008 | 0.4575          | 0.4390 | 0.6315 | 0.4530  | 0.1794  | 0.2343   | 0.3641 | 0.6128 | 0.7787 |
  | 0.4351        | 15.0  | 1080 | 0.4669          | 0.4373 | 0.6423 | 0.4322  | 0.1796  | 0.2423   | 0.3917 | 0.6233 | 0.7850 |
  | 0.4001        | 16.0  | 1152 | 0.4540          | 0.4356 | 0.6331 | 0.4336  | 0.1767  | 0.2320   | 0.3919 | 0.6132 | 0.7732 |
  | 0.3741        | 17.0  | 1224 | 0.4890          | 0.4645 | 0.6361 | 0.5707  | 0.1926  | 0.2494   | 0.3253 | 0.5469 | 0.7386 |
  | 0.4128        | 18.0  | 1296 | 0.4815          | 0.4593 | 0.6328 | 0.5511  | 0.1899  | 0.2457   | 0.3302 | 0.5571 | 0.7471 |
  | 0.3809        | 19.0  | 1368 | 0.5002          | 0.4768 | 0.6425 | 0.6061  | 0.1991  | 0.2560   | 0.3105 | 0.5222 | 0.7118 |
  | 0.4089        | 20.0  | 1440 | 0.4503          | 0.4311 | 0.6449 | 0.4081  | 0.1752  | 0.2370   | 0.4147 | 0.6445 | 0.7823 |
  | 0.3612        | 21.0  | 1512 | 0.4541          | 0.4280 | 0.6215 | 0.4543  | 0.1735  | 0.2302   | 0.3823 | 0.6291 | 0.7968 |
  | 0.3664        | 22.0  | 1584 | 0.4425          | 0.4251 | 0.6347 | 0.3970  | 0.1717  | 0.2300   | 0.4181 | 0.6374 | 0.7860 |
  | 0.3787        | 23.0  | 1656 | 0.4722          | 0.4477 | 0.6378 | 0.4868  | 0.1846  | 0.2432   | 0.3541 | 0.6041 | 0.7733 |
  | 0.4184        | 24.0  | 1728 | 0.4749          | 0.4506 | 0.6303 | 0.5329  | 0.1857  | 0.2434   | 0.3465 | 0.5752 | 0.7698 |
  | 0.3928        | 25.0  | 1800 | 0.4646          | 0.4485 | 0.6395 | 0.4744  | 0.1847  | 0.2407   | 0.3528 | 0.5946 | 0.7816 |
  | 0.3704        | 26.0  | 1872 | 0.4492          | 0.4340 | 0.6331 | 0.4344  | 0.1765  | 0.2326   | 0.3778 | 0.6314 | 0.7916 |
  | 0.3462        | 27.0  | 1944 | 0.4467          | 0.4307 | 0.6314 | 0.4296  | 0.1751  | 0.2317   | 0.3840 | 0.6359 | 0.7983 |
  | 0.3808        | 28.0  | 2016 | 0.4758          | 0.4622 | 0.633