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sayakpaul/glpn-nyu-finetuned-diode-221116-110652-glpn-nyu-finetuned-diode-22...

2026-08-08 0

sayakpaul/glpn-nyu-finetuned-diode-221116-110652-glpn-nyu-finetuned-diode-22...的重点在于把前置条件、操作顺序和容易误判的地方分清楚。

glpn-nyu-finetuned-diode-221116-110652

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:

Model description

More information needed

More information needed

More information needed

The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	Mae	Rmse	Abs Rel	Log Mae	Log Rmse	Delta1	Delta2	Delta3
1.3984	1.0	72	1.1606	3.2154	3.2710	4.6927	0.6627	0.7082	0.0	0.0053	0.0893
0.8305	2.0	144	0.5445	0.6035	0.8404	0.8013	0.2102	0.2726	0.2747	0.5358	0.7609
0.4601	3.0	216	0.4484	0.4041	0.5376	0.5417	0.1617	0.2188	0.3771	0.6932	0.8692
0.4211	4.0	288	0.4251	0.3634	0.4914	0.4800	0.1499	0.2069	0.4136	0.7270	0.8931
0.4162	5.0	360	0.4170	0.3537	0.4833	0.4483	0.1455	0.2005	0.4303	0.7444	0.8992
0.3776	6.0	432	0.4115	0.3491	0.4692	0.4558	0.1449	0.1999	0.4281	0.7471	0.9018
0.3729	7.0	504	0.4058	0.3337	0.4590	0.4135	0.1396	0.1935	0.4517	0.7652	0.9072
0.3235	8.0	576	0.4035	0.3304	0.4602	0.4043	0.1383	0.1929	0.4613	0.7679	0.9073
0.3382	9.0	648	0.3990	0.3254	0.4546	0.3937	0.1365	0.1900	0.4671	0.7717	0.9102
0.3265	10.0	720	0.4018	0.3272	0.4546	0.3934	0.1380	0.1907	0.4598	0.7659	0.9082

sayakpaul/glpn-nyu-finetuned-diode-221116-110652官网入口：https://huggingface.co/sayakpaul/glpn-nyu-finetuned-diode-221116-110652

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