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

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