---
license: apache-2.0
tags:
- vision
- depth-estimation
- generated_from_trainer
model-index:
- name: glpn-nyu-finetuned
  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

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: 1.5286
- Mae: 3.1196
- Rmse: 3.5796
- Abs Rel: 5.9353
- Log Mae: 0.6899
- Log Rmse: 0.8145
- Delta1: 0.3012
- Delta2: 0.3076
- Delta3: 0.3093

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mae    | Rmse   | Abs Rel | Log Mae | Log Rmse | Delta1 | Delta2 | Delta3 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:-------:|:--------:|:------:|:------:|:------:|
| No log        | 1.0   | 1    | 1.5476          | 3.2112 | 3.7133 | 6.1586  | 0.6980  | 0.8267   | 0.2998 | 0.3073 | 0.3091 |
| No log        | 2.0   | 2    | 1.5441          | 3.1939 | 3.6889 | 6.1181  | 0.6965  | 0.8245   | 0.3001 | 0.3073 | 0.3091 |
| No log        | 3.0   | 3    | 1.5410          | 3.1783 | 3.6668 | 6.0811  | 0.6951  | 0.8225   | 0.3003 | 0.3074 | 0.3092 |
| No log        | 4.0   | 4    | 1.5381          | 3.1643 | 3.6465 | 6.0474  | 0.6939  | 0.8207   | 0.3005 | 0.3074 | 0.3092 |
| No log        | 5.0   | 5    | 1.5355          | 3.1520 | 3.6285 | 6.0172  | 0.6928  | 0.8190   | 0.3007 | 0.3075 | 0.3092 |
| No log        | 6.0   | 6    | 1.5333          | 3.1415 | 3.6128 | 5.9909  | 0.6918  | 0.8176   | 0.3009 | 0.3075 | 0.3092 |
| No log        | 7.0   | 7    | 1.5315          | 3.1329 | 3.5999 | 5.9693  | 0.6911  | 0.8164   | 0.3010 | 0.3075 | 0.3093 |
| No log        | 8.0   | 8    | 1.5301          | 3.1264 | 3.5901 | 5.9529  | 0.6905  | 0.8155   | 0.3011 | 0.3075 | 0.3093 |
| No log        | 9.0   | 9    | 1.5291          | 3.1219 | 3.5832 | 5.9413  | 0.6901  | 0.8149   | 0.3012 | 0.3076 | 0.3093 |
| No log        | 10.0  | 10   | 1.5286          | 3.1196 | 3.5796 | 5.9353  | 0.6899  | 0.8145   | 0.3012 | 0.3076 | 0.3093 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3