glpn-nyu-finetuned-diode-221121-113853

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

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The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	Mae	Rmse	Abs Rel	Log Mae	Log Rmse	Delta1	Delta2	Delta3
0.7523	1.0	72	0.5772	0.7466	0.9116	0.9709	0.2568	0.3040	0.1373	0.3324	0.6328
0.4281	2.0	144	0.3849	0.3324	0.4673	0.3934	0.1349	0.1874	0.4681	0.7753	0.9142
0.3906	3.0	216	0.3660	0.3048	0.4418	0.3593	0.1258	0.1800	0.5225	0.7997	0.9195
0.3766	4.0	288	0.3556	0.2923	0.4275	0.3383	0.1209	0.1741	0.5450	0.8157	0.9259
0.3744	5.0	360	0.3539	0.2899	0.4171	0.3435	0.1208	0.1724	0.5355	0.8173	0.9307
0.328	6.0	432	0.3498	0.2860	0.4109	0.3418	0.1196	0.1709	0.5402	0.8193	0.9334
0.3166	7.0	504	0.3451	0.2793	0.4110	0.3203	0.1166	0.1677	0.5583	0.8286	0.9331
0.2639	8.0	576	0.3475	0.2823	0.4083	0.3341	0.1182	0.1695	0.5469	0.8251	0.9337
0.2802	9.0	648	0.3422	0.2779	0.4030	0.3249	0.1163	0.1667	0.5524	0.8287	0.9366
0.2701	10.0	720	0.3411	0.2781	0.3962	0.3316	0.1168	0.1664	0.5446	0.8286	0.9396
0.2232	11.0	792	0.3408	0.2755	0.3998	0.3259	0.1154	0.1665	0.5578	0.8332	0.9383
0.2921	12.0	864	0.3391	0.2749	0.3975	0.3220	0.1152	0.1652	0.5553	0.8332	0.9390
0.2837	13.0	936	0.3400	0.2745	0.3979	0.3251	0.1150	0.1660	0.5587	0.8347	0.9386
0.2922	14.0	1008	0.3370	0.2728	0.3965	0.3184	0.1142	0.1644	0.5602	0.8359	0.9401
0.2921	15.0	1080	0.3384	0.2739	0.3959	0.3230	0.1148	0.1651	0.5576	0.8345	0.9398