sayakpaul/glpn-nyu-finetuned-diode-230103-091356

2023-12-27 10:12 0 微浪网 0

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导语： glpn-nyu-finetuned-diode-23...,

Training Loss	Epoch	Step	Validation Loss	Mae	Rmse	Abs Rel	Log Mae	Log Rmse	Delta1	Delta2	Delta3
1.0762	1.0	72	0.5031	0.4779	0.6690	0.5503	0.2006	0.2591	0.3020	0.5337	0.8000
0.478	2.0	144	0.4653	0.4509	0.6307	0.4891	0.1861	0.2377	0.3300	0.5805	0.7734
0.4668	3.0	216	0.4845	0.4712	0.6373	0.5469	0.1963	0.2471	0.3110	0.5254	0.7235
0.4389	4.0	288	0.4587	0.4368	0.6219	0.4887	0.1787	0.2344	0.3578	0.6099	0.7926
0.4626	5.0	360	0.4879	0.4662	0.6351	0.5617	0.1937	0.2482	0.3135	0.5462	0.7395
0.4534	6.0	432	0.4638	0.4422	0.6236	0.4951	0.1810	0.2358	0.3606	0.5844	0.7831
0.4108	7.0	504	0.4688	0.4508	0.6279	0.5050	0.1856	0.2385	0.3426	0.5701	0.7623
0.3832	8.0	576	0.4759	0.4533	0.6284	0.5257	0.1869	0.2411	0.3331	0.5701	0.7617
0.4097	9.0	648	0.4771	0.4501	0.6303	0.5361	0.1855	0.2433	0.3454	0.5838	0.7609
0.3799	10.0	720	0.4575	0.4375	0.6240	0.4874	0.1790	0.2349	0.3669	0.6032	0.7916
0.3659	11.0	792	0.4718	0.4590	0.6298	0.5176	0.1893	0.2396	0.3283	0.5502	0.7368
0.4145	12.0	864	0.4776	0.4561	0.6298	0.5325	0.1883	0.2421	0.3333	0.5611	0.7540
0.4224	13.0	936	0.4320	0.4138	0.6202	0.4013	0.1655	0.2232	0.4217	0.6641	0.8004
0.4142	14.0	1008	0.4597	0.4440	0.6234	0.4842	0.1813	0.2330	0.3520	0.5895	0.7617
0.4393	15.0	1080	0.4333	0.4251	0.6197	0.4182	0.1712	0.2225	0.3787	0.6303	0.8100
0.4045	16.0	1152	0.4603	0.4356	0.6197	0.4819	0.1776	0.2322	0.3635	0.6050	0.7858
0.3708	17.0	1224	0.4738	0.4567	0.6292	0.5264	0.1886	0.2411	0.3283	0.5557	0.7596
0.4042	18.0	1296	0.5004	0.4802	0.6423	0.6101	0.2008	0.2560	0.3022	0.5165	0.6931
0.3763	19.0	1368	0.4501	0.4361	0.6213	0.4723	0.1772	0.2303	0.3634	0.6034	0.7889
0.4084	20.0	1440	0.4272	0.4133	0.6208	0.3958	0.1649	0.2226	0.4284	0.6684	0.8009
0.3637	21.0	1512	0.4307	0.4145	0.6199	0.4134	0.1665	0.2241	0.3957	0.6847	0.8137
0.3655	22.0	1584	0.4591	0.4374	0.6370	0.4594	0.1791	0.2384	0.3816	0.6264	0.7826
0.3844	23.0	1656	0.4692	0.4444	0.6273	0.5241	0.1824	0.2407	0.3540	0.5990	0.7756
0.428	24.0	1728	0.4982	0.4753	0.6403	0.6084	0.1984	0.2552	0.3099	0.5233	0.7204
0.4051	25.0	1800	0.4824	0.4618	0.6329	0.5533	0.1915	0.2461	0.3248	0.5495	0.7415
0.3584	26.0	1872	0.4434	0.4207	0.6177	0.4468	0.1694	0.2277	0.3975	0.6442	0.8038
0.3443	27.0	1944	0.4602	0.4434	0.6241	0.4912	0.1822	0.2351	0.3431	0.5877	0.7893
0.3714	28.0	2016	0.4818	0.4594	0.6316	0.5521	0.1900	0.2455	0.3283	0.5567	0.7493
0.3688	29.0	2088	0.4443	0.4215	0.6242	0.4386	0.1702	0.2294	0.4024	0.6522	0.8065
0.3615	30.0	2160	0.4462	0.4291	0.6189	0.4500	0.1739	0.2277	0.3792	0.6208	0.7896
0.3655	31.0	2232	0.4808	0.4574	0.6305	0.5524	0.1893	0.2452	0.3322	0.5590	0.7460
0.3576	32.0	2304	0.4321	0.4102	0.6182	0.4079	0.1640	0.2241	0.4296	0.6713	0.8074
0.3947	33.0	2376	0.4468	0.4298	0.6232	0.4574	0.1744	0.2306	0.3873	0.6163	0.7873
0.3402	34.0	2448	0.4565	0.4352	0.6195	0.4913	0.1776	0.2337	0.3734	0.6039	0.7865
0.3412	35.0	2520	0.4438	0.4261	0.6180	0.4546	0.1728	0.2279	0.3778	0.6252	0.8043
0.3547	36.0	2592	0.4577	0.4416	0.6218	0.4868	0.1807	0.2329	0.3517	0.5862	0.7862
0.3425	37.0	2664	0.4682	0.4511	0.6285	0.5210	0.1860	0.2406	0.3411	0.5748	0.7694
0.3853	38.0	2736	0.4752	0.4514	0.6289	0.5458	0.1863	0.2438	0.3408	0.5721	0.7760
0.3643	39.0	2808	0.4737	0.4547	0.6291	0.5401	0.1875	0.2428	0.3316	0.5673	0.7617
0.398	40.0	2880	0.4662	0.4467	0.6274	0.5124	0.1838	0.2394	0.3514	0.5823	0.7700
0.3579	41.0	2952	0.4781	0.4545	0.6290	0.5513	0.1880	0.2446	0.3343	0.5624	0.7718
0.3545	42.0	3024	0.4460	0.4277	0.6221	0.4553	0.1730	0.2294	0.3862	0.6285	0.7999
0.3527	43.0	3096	0.4330	0.4153	0.6169	0.4221	0.1668	0.2240	0.4106	0.6618	0.8084
0.3251	44.0	3168	0.4503	0.4286	0.6172	0.4781	0.1744	0.2313	0.3725	0.6224	0.8095
0.3433	45.0	3240	0.4471	0.4346	0.6187	0.4652	0.1772	0.2293	0.3606	0.6043	0.7952
0.3607	46.0	3312	0.4474	0.4263	0.6166	0.4658	0.1728	0.2293	0.3835	0.6287	0.8039
0.3722	47.0	3384	0.4527	0.4337	0.6205	0.4857	0.1768	0.2329	0.3696	0.6084	0.7922
0.3322	48.0	3456	0.4629	0.4431	0.6236	0.5118	0.1818	0.2373	0.3460	0.5897	0.7954
0.3624	49.0	3528	0.4431	0.4304	0.6203	0.4511	0.1742	0.2277	0.3827	0.6152	0.7917
0.3386	50.0	3600	0.4475	0.4260	0.6173	0.4697	0.1727	0.2301	0.3870	0.6283	0.8102
0.3316	51.0	3672	0.4558	0.4328	0.6194	0.4982	0.1770	0.2345	0.3618	0.6120	0.8124
0.3259	52.0	3744	0.4316	0.4084	0.6165	0.4234	0.1630	0.2245	0.4311	0.6809	0.8148
0.3299	53.0	3816	0.4489	0.4222	0.6198	0.4779	0.1706	0.2327	0.4049	0.6441	0.8021
0.3334	54.0	3888	0.4831	0.4598	0.6319	0.5716	0.1902	0.2476	0.3281	0.5597	0.7549
0.3342	55.0	3960	0.4478	0.4288	0.6166	0.4786	0.1745	0.2310	0.3749	0.6218	0.8091
0.3276	56.0	4032	0.4524	0.4342	0.6192	0.4852	0.1773	0.2326	0.3596	0.6113	0.8007
0.326	57.0	4104	0.4411	0.4226	0.6162	0.4486	0.1704	0.2268	0.3947	0.6403	0.7959
0.3429	58.0	4176	0.4578	0.4418	0.6221	0.4961	0.1812	0.2349	0.3497	0.5956	0.7750
0.3347	59.0	4248	0.4586	0.4409	0.6220	0.4946	0.1808	0.2347	0.3439	0.6004	0.7869
0.3215	60.0	4320	0.4583	0.4382	0.6232	0.4974	0.1789	0.2357	0.3667	0.6008	0.7855
0.331	61.0	4392	0.4412	0.4206	0.6145	0.4579	0.1699	0.2276	0.3966	0.6413	0.8047
0.3124	62.0	4464	0.4455	0.4236	0.6181	0.4727	0.1715	0.2313	0.3902	0.6417	0.8098
0.322	63.0	4536	0.4406	0.4230	0.6143	0.4548	0.1716	0.2269	0.3775	0.6425	0.8115
0.3194	64.0	4608	0.4473	0.4331	0.6193	0.4657	0.1765	0.2297	0.3606	0.6122	0.8014
0.3159	65.0	4680	0.4407	0.4225	0.6186	0.4548	0.1712	0.2293	0.3913	0.6433	0.8075
0.3118	66.0	4752	0.4478	0.4258	0.6169	0.4801	0.1728	0.2315	0.3762	0.6391	0.8064
0.336	67.0	4824	0.4659	0.4463	0.6252	0.5210	0.1834	0.2394	0.3464	0.5820	0.7786
0.3233	68.0	4896	0.4370	0.4208	0.6168	0.4452	0.1696	0.2265	0.4019	0.6425	0.8059
0.3285	69.0	4968	0.4479	0.4340	0.6189	0.4773	0.1771	0.2312	0.3609	0.6136	0.7972
0.3186	70.0	5040	0.4469	0.4308	0.6198	0.4698	0.1751	0.2310	0.3741	0.6219	0.7966
0.3351	71.0	5112	0.4476	0.4292	0.6176	0.4769	0.1745	0.2311	0.3718	0.6220	0.8035
0.3286	72.0	5184	0.4415	0.4229	0.6155	0.4655	0.1713	0.2289	0.3816	0.6376	0.8117
0.3135	73.0	5256	0.4527	0.4335	0.6198	0.4918	0.1769	0.2338	0.3621	0.6152	0.8036
0.3244	74.0	5328	0.4449	0.4290	0.6171	0.4685	0.1746	0.2296	0.3667	0.6234	0.8073
0.3253	75.0	5400	0.4450	0.4303	0.6182	0.4680	0.1750	0.2296	0.3703	0.6185	0.8013
0.3072	76.0	5472	0.4312	0.4212	0.6161	0.4337	0.1700	0.2242	0.3840	0.6411	0.8104
0.3159	77.0	5544	0.4434	0.4314	0.6186	0.4636	0.1754	0.2290	0.3643	0.6171	0.7996
0.3176	78.0	5616	0.4319	0.4207	0.6177	0.4330	0.1695	0.2249	0.3889	0.6524	0.8080
0.3243	79.0	5688	0.4432	0.4304	0.6186	0.4698	0.1752	0.2302	0.3667	0.6218	0.8058
0.3183	80.0	5760	0.4438	0.4288	0.6175	0.4665	0.1742	0.2294	0.3730	0.6235	0.8030
0.323	81.0	5832	0.4365	0.4248	0.6170	0.4480	0.1716	0.2263	0.3820	0.6313	0.8056
0.3348	82.0	5904	0.4385	0.4280	0.6179	0.4532	0.1738	0.2273	0.3651	0.6249	0.8099
0.2948	83.0	5976	0.4456	0.4330	0.6190	0.4727	0.1763	0.2305	0.3622	0.6121	0.7981
0.3156	84.0	6048	0.4349	0.4236	0.6155	0.4442	0.1712	0.2252	0.3834	0.6331	0.8086
0.3227	85.0	6120	0.4352	0.4251	0.6160	0.4423	0.1719	0.2250	0.3799	0.6293	0.8055
0.3044	86.0	6192	0.4349	0.4235	0.6165	0.4444	0.1714	0.2259	0.3858	0.6312	0.8108
0.3067	87.0	6264	0.4293	0.4214	0.6150	0.4293	0.1700	0.2229	0.3862	0.6397	0.8102
0.3083	88.0	6336	0.4260	0.4164	0.6139	0.4229	0.1673	0.2221	0.3989	0.6536	0.8126
0.2989	89.0	6408	0.4381	0.4270	0.6168	0.4526	0.1731	0.2270	0.3766	0.6248	0.8051
0.3232	90.0	6480	0.4352	0.4230	0.6158	0.4480	0.1711	0.2263	0.3854	0.6358	0.8112
0.3201	91.0	6552	0.4361	0.4242	0.6164	0.4462	0.1718	0.2262	0.3842	0.6327	0.8078
0.3096	92.0	6624	0.4390	0.4273	0.6171	0.4563	0.1733	0.2279	0.3790	0.6237	0.8046
0.322	93.0	6696	0.4338	0.4229	0.6157	0.4447	0.1709	0.2258	0.3889	0.6351	0.8069
0.3096	94.0	6768	0.4348	0.4238	0.6160	0.4448	0.1714	0.2256	0.3839	0.6342	0.8077
0.3067	95.0	6840	0.4414	0.4298	0.6181	0.4628	0.1748	0.2290	0.3707	0.6205	0.8027
0.3198	96.0	6912	0.4334	0.4228	0.6162	0.4434	0.1709	0.2258	0.3872	0.6370	0.8077
0.295	97.0	6984	0.4367	0.4261	0.6169	0.4507	0.1728	0.2269	0.3791	0.6283	0.8045
0.305	98.0	7056	0.4373	0.4266	0.6171	0.4524	0.1730	0.2273	0.3781	0.6280	0.8046
0.3304	99.0	7128	0.4334	0.4230	0.6162	0.4432	0.1709	0.2257	0.3874	0.6378	0.8062
0.3099	100.0	7200	0.4360	0.4251	0.6169	0.4500	0.1721	0.2269	0.3828	0.6326	0.8051

glpn-nyu-finetuned-diode-230103-091356

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: 0.4360

Mae: 0.4251

Rmse: 0.6169

Abs Rel: 0.4500

Log Mae: 0.1721

Log Rmse: 0.2269

Delta1: 0.3828

Delta2: 0.6326

Delta3: 0.8051

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: 0.0003

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: 0.15

num_epochs: 100

mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Mae Rmse Abs Rel Log Mae Log Rmse Delta1 Delta2 Delta3

1.0762 1.0 72 0.5031 0.4779 0.6690 0.5503 0.2006 0.2591 0.3020 0.5337 0.8000

0.478 2.0 144 0.4653 0.4509 0.6307 0.4891 0.1861 0.2377 0.3300 0.5805 0.7734

0.4668 3.0 216 0.4845 0.4712 0.6373 0.5469 0.1963 0.2471 0.3110 0.5254 0.7235

0.4389 4.0 288 0.4587 0.4368 0.6219 0.4887 0.1787 0.2344 0.3578 0.6099 0.7926

0.4626 5.0 360 0.4879 0.4662 0.6351 0.5617 0.1937 0.2482 0.3135 0.5462 0.7395

0.4534 6.0 432 0.4638 0.4422 0.6236 0.4951 0.1810 0.2358 0.3606 0.5844 0.7831

0.4108 7.0 504 0.4688 0.4508 0.6279 0.5050 0.1856 0.2385 0.3426 0.5701 0.7623

0.3832 8.0 576 0.4759 0.4533 0.6284 0.5257 0.1869 0.2411 0.3331 0.5701 0.7617

0.4097 9.0 648 0.4771 0.4501 0.6303 0.5361 0.1855 0.2433 0.3454 0.5838 0.7609

0.3799 10.0 720 0.4575 0.4375 0.6240 0.4874 0.1790 0.2349 0.3669 0.6032 0.7916

0.3659 11.0 792 0.4718 0.4590 0.6298 0.5176 0.1893 0.2396 0.3283 0.5502 0.7368

0.4145 12.0 864 0.4776 0.4561 0.6298 0.5325 0.1883 0.2421 0.3333 0.5611 0.7540

0.4224 13.0 936 0.4320 0.4138 0.6202 0.4013 0.1655 0.2232 0.4217 0.6641 0.8004

0.4142 14.0 1008 0.4597 0.4440 0.6234 0.4842 0.1813 0.2330 0.3520 0.5895 0.7617

0.4393 15.0 1080 0.4333 0.4251 0.6197 0.4182 0.1712 0.2225 0.3787 0.6303 0.8100

0.4045 16.0 1152 0.4603 0.4356 0.6197 0.4819 0.1776 0.2322 0.3635 0.6050 0.7858

0.3708 17.0 1224 0.4738 0.4567 0.6292 0.5264 0.1886 0.2411 0.3283 0.5557 0.7596

0.4042 18.0 1296 0.5004 0.4802 0.6423 0.6101 0.2008 0.2560 0.3022 0.5165 0.6931

0.3763 19.0 1368 0.4501 0.4361 0.6213 0.4723 0.1772 0.2303 0.3634 0.6034 0.7889

0.4084 20.0 1440 0.4272 0.4133 0.6208 0.3958 0.1649 0.2226 0.4284 0.6684 0.8009

0.3637 21.0 1512 0.4307 0.4145 0.6199 0.4134 0.1665 0.2241 0.3957 0.6847 0.8137

0.3655 22.0 1584 0.4591 0.4374 0.6370 0.4594 0.1791 0.2384 0.3816 0.6264 0.7826

0.3844 23.0 1656 0.4692 0.4444 0.6273 0.5241 0.1824 0.2407 0.3540 0.5990 0.7756

0.428 24.0 1728 0.4982 0.4753 0.6403 0.6084 0.1984 0.2552 0.3099 0.5233 0.7204

0.4051 25.0 1800 0.4824 0.4618 0.6329 0.5533 0.1915 0.2461 0.3248 0.5495 0.7415

0.3584 26.0 1872 0.4434 0.4207 0.6177 0.4468 0.1694 0.2277 0.3975 0.6442 0.8038

0.3443 27.0 1944 0.4602 0.4434 0.6241 0.4912 0.1822 0.2351 0.3431 0.5877 0.7893

0.3714 28.0 2016 0.4818 0.4594 0.6316 0.5521 0.1900 0.2455 0.3283 0.5567 0.7493

0.3688 29.0 2088 0.4443 0.4215 0.6242 0.4386 0.1702 0.2294 0.4024 0.6522 0.8065

0.3615 30.0 2160 0.4462 0.4291 0.6189 0.4500 0.1739 0.2277 0.3792 0.6208 0.7896

0.3655 31.0 2232 0.4808 0.4574 0.6305 0.5524 0.1893 0.2452 0.3322 0.5590 0.7460

0.3576 32.0 2304 0.4321 0.4102 0.6182 0.4079 0.1640 0.2241 0.4296 0.6713 0.8074

0.3947 33.0 2376 0.4468 0.4298 0.6232 0.4574 0.1744 0.2306 0.3873 0.6163 0.7873

0.3402 34.0 2448 0.4565 0.4352 0.6195 0.4913 0.1776 0.2337 0.3734 0.6039 0.7865

0.3412 35.0 2520 0.4438 0.4261 0.6180 0.4546 0.1728 0.2279 0.3778 0.6252 0.8043

0.3547 36.0 2592 0.4577 0.4416 0.6218 0.4868 0.1807 0.2329 0.3517 0.5862 0.7862

0.3425 37.0 2664 0.4682 0.4511 0.6285 0.5210 0.1860 0.2406 0.3411 0.5748 0.7694

0.3853 38.0 2736 0.4752 0.4514 0.6289 0.5458 0.1863 0.2438 0.3408 0.5721 0.7760

0.3643 39.0 2808 0.4737 0.4547 0.6291 0.5401 0.1875 0.2428 0.3316 0.5673 0.7617

0.398 40.0 2880 0.4662 0.4467 0.6274 0.5124 0.1838 0.2394 0.3514 0.5823 0.7700

0.3579 41.0 2952 0.4781 0.4545 0.6290 0.5513 0.1880 0.2446 0.3343 0.5624 0.7718

0.3545 42.0 3024 0.4460 0.4277 0.6221 0.4553 0.1730 0.2294 0.3862 0.6285 0.7999

0.3527 43.0 3096 0.4330 0.4153 0.6169 0.4221 0.1668 0.2240 0.4106 0.6618 0.8084

0.3251 44.0 3168 0.4503 0.4286 0.6172 0.4781 0.1744 0.2313 0.3725 0.6224 0.8095

0.3433 45.0 3240 0.4471 0.4346 0.6187 0.4652 0.1772 0.2293 0.3606 0.6043 0.7952

0.3607 46.0 3312 0.4474 0.4263 0.6166 0.4658 0.1728 0.2293 0.3835 0.6287 0.8039

0.3722 47.0 3384 0.4527 0.4337 0.6205 0.4857 0.1768 0.2329 0.3696 0.6084 0.7922

0.3322 48.0 3456 0.4629 0.4431 0.6236 0.5118 0.1818 0.2373 0.3460 0.5897 0.7954

0.3624 49.0 3528 0.4431 0.4304 0.6203 0.4511 0.1742 0.2277 0.3827 0.6152 0.7917

0.3386 50.0 3600 0.4475 0.4260 0.6173 0.4697 0.1727 0.2301 0.3870 0.6283 0.8102

0.3316 51.0 3672 0.4558 0.4328 0.6194 0.4982 0.1770 0.2345 0.3618 0.6120 0.8124

0.3259 52.0 3744 0.4316 0.4084 0.6165 0.4234 0.1630 0.2245 0.4311 0.6809 0.8148

0.3299 53.0 3816 0.4489 0.4222 0.6198 0.4779 0.1706 0.2327 0.4049 0.6441 0.8021

0.3334 54.0 3888 0.4831 0.4598 0.6319 0.5716 0.1902 0.2476 0.3281 0.5597 0.7549

0.3342 55.0 3960 0.4478 0.4288 0.6166 0.4786 0.1745 0.2310 0.3749 0.6218 0.8091

0.3276 56.0 4032 0.4524 0.4342 0.6192 0.4852 0.1773 0.2326 0.3596 0.6113 0.8007

0.326 57.0 4104 0.4411 0.4226 0.6162 0.4486 0.1704 0.2268 0.3947 0.6403 0.7959

0.3429 58.0 4176 0.4578 0.4418 0.6221 0.4961 0.1812 0.2349 0.3497 0.5956 0.7750

0.3347 59.0 4248 0.4586 0.4409 0.6220 0.4946 0.1808 0.2347 0.3439 0.6004 0.7869

0.3215 60.0 4320 0.4583 0.4382 0.6232 0.4974 0.1789 0.2357 0.3667 0.6008 0.7855

0.331 61.0 4392 0.4412 0.4206 0.6145 0.4579 0.1699 0.2276 0.3966 0.6413 0.8047

0.3124 62.0 4464 0.4455 0.4236 0.6181 0.4727 0.1715 0.2313 0.3902 0.6417 0.8098

0.322 63.0 4536 0.4406 0.4230 0.6143 0.4548 0.1716 0.2269 0.3775 0.6425 0.8115

0.3194 64.0 4608 0.4473 0.4331 0.6193 0.4657 0.1765 0.2297 0.3606 0.6122 0.8014

0.3159 65.0 4680 0.4407 0.4225 0.6186 0.4548 0.1712 0.2293 0.3913 0.6433 0.8075

0.3118 66.0 4752 0.4478 0.4258 0.6169 0.4801 0.1728 0.2315 0.3762 0.6391 0.8064

0.336 67.0 4824 0.4659 0.4463 0.6252 0.5210 0.1834 0.2394 0.3464 0.5820 0.7786

0.3233 68.0 4896 0.4370 0.4208 0.6168 0.4452 0.1696 0.2265 0.4019 0.6425 0.8059

0.3285 69.0 4968 0.4479 0.4340 0.6189 0.4773 0.1771 0.2312 0.3609 0.6136 0.7972

0.3186 70.0 5040 0.4469 0.4308 0.6198 0.4698 0.1751 0.2310 0.3741 0.6219 0.7966

0.3351 71.0 5112 0.4476 0.4292 0.6176 0.4769 0.1745 0.2311 0.3718 0.6220 0.8035

0.3286 72.0 5184 0.4415 0.4229 0.6155 0.4655 0.1713 0.2289 0.3816 0.6376 0.8117

0.3135 73.0 5256 0.4527 0.4335 0.6198 0.4918 0.1769 0.2338 0.3621 0.6152 0.8036

0.3244 74.0 5328 0.4449 0.4290 0.6171 0.4685 0.1746 0.2296 0.3667 0.6234 0.8073

0.3253 75.0 5400 0.4450 0.4303 0.6182 0.4680 0.1750 0.2296 0.3703 0.6185 0.8013

0.3072 76.0 5472 0.4312 0.4212 0.6161 0.4337 0.1700 0.2242 0.3840 0.6411 0.8104

0.3159 77.0 5544 0.4434 0.4314 0.6186 0.4636 0.1754 0.2290 0.3643 0.6171 0.7996

0.3176 78.0 5616 0.4319 0.4207 0.6177 0.4330 0.1695 0.2249 0.3889 0.6524 0.8080

0.3243 79.0 5688 0.4432 0.4304 0.6186 0.4698 0.1752 0.2302 0.3667 0.6218 0.8058

0.3183 80.0 5760 0.4438 0.4288 0.6175 0.4665 0.1742 0.2294 0.3730 0.6235 0.8030

0.323 81.0 5832 0.4365 0.4248 0.6170 0.4480 0.1716 0.2263 0.3820 0.6313 0.8056

0.3348 82.0 5904 0.4385 0.4280 0.6179 0.4532 0.1738 0.2273 0.3651 0.6249 0.8099

0.2948 83.0 5976 0.4456 0.4330 0.6190 0.4727 0.1763 0.2305 0.3622 0.6121 0.7981

0.3156 84.0 6048 0.4349 0.4236 0.6155 0.4442 0.1712 0.2252 0.3834 0.6331 0.8086

0.3227 85.0 6120 0.4352 0.4251 0.6160 0.4423 0.1719 0.2250 0.3799 0.6293 0.8055

0.3044 86.0 6192 0.4349 0.4235 0.6165 0.4444 0.1714 0.2259 0.3858 0.6312 0.8108

0.3067 87.0 6264 0.4293 0.4214 0.6150 0.4293 0.1700 0.2229 0.3862 0.6397 0.8102

0.3083 88.0 6336 0.4260 0.4164 0.6139 0.4229 0.1673 0.2221 0.3989 0.6536 0.8126

0.2989 89.0 6408 0.4381 0.4270 0.6168 0.4526 0.1731 0.2270 0.3766 0.6248 0.8051

0.3232 90.0 6480 0.4352 0.4230 0.6158 0.4480 0.1711 0.2263 0.3854 0.6358 0.8112

0.3201 91.0 6552 0.4361 0.4242 0.6164 0.4462 0.1718 0.2262 0.3842 0.6327 0.8078

0.3096 92.0 6624 0.4390 0.4273 0.6171 0.4563 0.1733 0.2279 0.3790 0.6237 0.8046

0.322 93.0 6696 0.4338 0.4229 0.6157 0.4447 0.1709 0.2258 0.3889 0.6351 0.8069

0.3096 94.0 6768 0.4348 0.4238 0.6160 0.4448 0.1714 0.2256 0.3839 0.6342 0.8077

0.3067 95.0 6840 0.4414 0.4298 0.6181 0.4628 0.1748 0.2290 0.3707 0.6205 0.8027

0.3198 96.0 6912 0.4334 0.4228 0.6162 0.4434 0.1709 0.2258 0.3872 0.6370 0.8077

0.295 97.0 6984 0.4367 0.4261 0.6169 0.4507 0.1728 0.2269 0.3791 0.6283 0.8045

0.305 98.0 7056 0.4373 0.4266 0.6171 0.4524 0.1730 0.2273 0.3781 0.6280 0.8046

0.3304 99.0 7128 0.4334 0.4230 0.6162 0.4432 0.1709 0.2257 0.3874 0.6378 0.8062

0.3099 100.0 7200 0.4360 0.4251 0.6169 0.4500 0.1721 0.2269 0.3828 0.6326 0.8051

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sayakpaul/glpn-nyu-finetuned-diode-230103-091356

glpn-nyu-finetuned-diode-230103-091356

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

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