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# glpn-nyu-finetuned-diode-230530-204740

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: 1.5139
- Mae: 3.0509
- Rmse: 3.4756
- Abs Rel: 5.7613
- Log Mae: 0.6836
- Log Rmse: 0.8048
- Delta1: 0.3028
- Delta2: 0.3079
- Delta3: 0.3096

## 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    | 1.5335          | 3.1427 | 3.6089 | 5.9847  | 0.6920  | 0.8173   | 0.3016 | 0.3077 | 0.3094 |
| No log        | 2.0   | 2    | 1.5297          | 3.1246 | 3.5833 | 5.9419  | 0.6903  | 0.8149   | 0.3018 | 0.3077 | 0.3094 |
| No log        | 3.0   | 3    | 1.5263          | 3.1085 | 3.5602 | 5.9033  | 0.6889  | 0.8128   | 0.3020 | 0.3078 | 0.3095 |
| No log        | 4.0   | 4    | 1.5234          | 3.0947 | 3.5400 | 5.8694  | 0.6876  | 0.8109   | 0.3022 | 0.3078 | 0.3095 |
| No log        | 5.0   | 5    | 1.5208          | 3.0825 | 3.5222 | 5.8395  | 0.6865  | 0.8092   | 0.3024 | 0.3079 | 0.3095 |
| No log        | 6.0   | 6    | 1.5185          | 3.0723 | 3.5072 | 5.8144  | 0.6856  | 0.8078   | 0.3025 | 0.3079 | 0.3095 |
| No log        | 7.0   | 7    | 1.5167          | 3.0639 | 3.4949 | 5.7937  | 0.6848  | 0.8067   | 0.3026 | 0.3079 | 0.3096 |
| No log        | 8.0   | 8    | 1.5153          | 3.0574 | 3.4852 | 5.7775  | 0.6842  | 0.8057   | 0.3027 | 0.3079 | 0.3096 |
| No log        | 9.0   | 9    | 1.5143          | 3.0531 | 3.4788 | 5.7667  | 0.6838  | 0.8051   | 0.3028 | 0.3079 | 0.3096 |
| No log        | 10.0  | 10   | 1.5139          | 3.0509 | 3.4756 | 5.7613  | 0.6836  | 0.8048   | 0.3028 | 0.3079 | 0.3096 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["vision", "depth-estimation", "generated_from_trainer"], "model-index": [{"name": "glpn-nyu-finetuned-diode-230530-204740", "results": []}]}
transformers pytorch glpn depth-estimation vision generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #glpn #depth-estimation #vision #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

glpn-nyu-finetuned-diode-230530-204740
======================================


This model is a fine-tuned version of vinvino02/glpn-nyu on the diode-subset dataset.
It achieves the following results on the evaluation set:


* Loss: 1.5139
* Mae: 3.0509
* Rmse: 3.4756
* Abs Rel: 5.7613
* Log Mae: 0.6836
* Log Rmse: 0.8048
* Delta1: 0.3028
* Delta2: 0.3079
* Delta3: 0.3096


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



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Tokenizers 0.13.3



### 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 ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #glpn #depth-estimation #vision #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Tokenizers 0.13.3