readme: ---
  license: apache-2.0
  tags:
  - vision
  - depth-estimation
  - generated_from_trainer
  model-index:
  - name: glpn-kitti-finetuned-diode
    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-kitti-finetuned-diode
  
  This model is a fine-tuned version of [vinvino02/glpn-kitti](https://huggingface.co/vinvino02/glpn-kitti) on the diode-subset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5845
  - Rmse: 0.6175
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rmse   |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.0   | 10   | 0.8001          | 0.8455 |
  | 0.8187        | 2.0   | 20   | 0.7558          | 0.7907 |
  | 0.8187        | 3.0   | 30   | 0.7391          | 0.7379 |
  | 0.7618        | 4.0   | 40   | 0.6937          | 0.6895 |
  | 0.7618        | 5.0   | 50   | 0.6954          | nan    |
  | 0.6917        | 6.0   | 60   | 0.6834          | nan    |
  | 0.6917        | 7.0   | 70   | 0.6719          | nan    |
  | 0.6625        | 8.0   | 80   | 0.6634          | nan    |
  | 0.6625        | 9.0   | 90   | 0.6592          | nan    |
  | 0.6553        | 10.0  | 100  | 0.6579          | nan    |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Tokenizers 0.13.2
  