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Glpn Nyu Finetuned Diode 230530 193901

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: 1.5356 Mae: 3.1497 Rmse: 3.6237 Abs Rel: 6.0096 Log Mae: 0.6926 Log...

Sourcehuggingface.co/Onegafer/glpn-nyu-finetuned-diode-230530-193901/tree/4dad37f29a2f061fea22d0d2d789e9723a1787f9
TypeOtherVersionRevision 4dad37fBClasse

Source du modèle

Type
Other
Taille du fichier
234 MB
Version
vRevision 4dad37f
Mis à jour
8 oct. 2026
Téléchargements
8
Source
Hugging Face

Description de la source

glpn-nyu-finetuned-diode-230530-193901

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: 1.5356
  • Mae: 3.1497
  • Rmse: 3.6237
  • Abs Rel: 6.0096
  • Log Mae: 0.6926
  • Log Rmse: 0.8186
  • Delta1: 0.3020
  • Delta2: 0.3077
  • Delta3: 0.3094

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 LossEpochStepValidation LossMaeRmseAbs RelLog MaeLog RmseDelta1Delta2Delta3
No log1.011.56043.27683.80486.31110.70370.83470.29960.30730.3091
No log2.021.55593.25363.77316.25840.70170.83190.29980.30730.3092
No log3.031.55133.22983.74016.20340.69970.82900.30020.30740.3092
No log4.041.54693.20763.70836.15060.69770.82620.30060.30750.3093
No log5.051.54343.18943.68156.10600.69610.82380.30110.30750.3093
No log6.061.54073.17573.66146.07250.69490.82200.30150.30760.3094
No log7.071.53873.16523.64606.04680.69400.82070.30170.30760.3094
No log8.081.53713.15743.63486.02810.69330.81960.30190.30770.3094
No log9.091.53613.15233.62736.01570.69280.81900.30200.30770.3094
No log10.0101.53563.14973.62376.00960.69260.81860.30200.30770.3094

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.0.1+cu118
  • Tokenizers 0.13.3

Sources

1 source
Hugging FacePrincipalVersion 4dad37f29a2f061fea22d0d2d789e9723a1787f9
huggingface.co/Onegafer/glpn-nyu-finetuned-diode-230530-193901/tree/4dad37f29a2f061fea22d0d2d789e9723a1787f9

Vérifié 25 août

Artefacts du modèle

1 artefact

pytorch_model.bin

bin · 234 MB · SHA-256 df8b60576334…ff8f · Hugging Face

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Extraits de sources

2 extraits
Readme25 aoûthuggingface.co/Onegafer/glpn-nyu-finetuned-diode-230530-193901

--- license: apache-2.0 tags: - vision - depth-estimation - generated_from_trainer model-index: - name: glpn-nyu-finetuned-diode-230530-193901 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-230530-193901 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: 1.5356 - Mae: 3.1497 - Rmse: 3.6237 - Abs Rel: 6.0096 - Log Mae: 0.6926 - Log Rmse: 0.8186 - Delta1: 0.3020 - Delta2: 0.3077 - Delta3: 0.3094 ## 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 | 1.5604 | 3.2768 | 3.8048 | 6.3111 | 0.7037 | 0.8347 | 0.2996 | 0.3073 | 0.3091 | | No log | 2.0 | 2 | 1.5559 | 3.2536 | 3.7731 | 6.2584 | 0.7017 | 0.8319 | 0.2998 | 0.3073 | 0.3092 | | No log | 3.0 | 3 | 1.5513 | 3.2298 | 3.7401 | 6.2034 | 0.6997 | 0.8290 | 0.3002 | 0.3074 | 0.3092 | | No log | 4.0 | 4 | 1.5469 | 3.2076 | 3.7083 | 6.1506 | 0.6977 | 0.8262 | 0.3006 | 0.3075 | 0.3093 | | No log | 5.0 | 5 | 1.5434 | 3.1894 | 3.6815 | 6.1060 | 0.6961 | 0.8238 | 0.3011 | 0.3075 | 0.3093 | | No log | 6.0 | 6 | 1.5407 | 3.1757 | 3.6614 | 6.0725 | 0.6949 | 0.8220 | 0.3015 | 0.3076 | 0.3094 | | No log | 7.0 | 7 | 1.5387 | 3.1652 | 3.6460 | 6.0468 | 0.6940 | 0.8207 | 0.3017 | 0.3076 | 0.3094 | | No log | 8.0 | 8 | 1.5371 | 3.1574 | 3.6348 | 6.0281 | 0.6933 | 0.8196 | 0.3019 | 0.3077 | 0.3094 | | No log | 9.0 | 9 | 1.5361 | 3.1523 | 3.6273 | 6....

Note25 aoûthuggingface.co/Onegafer/glpn-nyu-finetuned-diode-230530-193901

Source context: 8 downloads · 0 likes · Pipeline depth-estimation · Library transformers · Repo Onegafer/glpn-nyu-finetuned-diode-230530-193901