glpn-nyu-finetuned-diode-221214-081122

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: 0.3242
Mae: 0.2603
Rmse: 0.3997
Abs Rel: 0.3010
Log Mae: 0.1073
Log Rmse: 0.1624
Delta1: 0.6187
Delta2: 0.8455
Delta3: 0.9378

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: 5e-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: 0.15
num_epochs: 25
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Mae	Rmse	Abs Rel	Log Mae	Log Rmse	Delta1	Delta2	Delta3
0.6896	1.0	72	0.4753	0.4670	0.6226	0.5658	0.1791	0.2313	0.2950	0.6310	0.8562
0.3628	2.0	144	0.3565	0.2956	0.4307	0.3421	0.1226	0.1737	0.5285	0.8079	0.9245
0.3168	3.0	216	0.3486	0.2774	0.3963	0.3464	0.1172	0.1710	0.5561	0.8285	0.9358
0.2734	4.0	288	0.3368	0.2669	0.3962	0.3260	0.1122	0.1671	0.5787	0.8453	0.9383
0.2678	5.0	360	0.3419	0.2700	0.4136	0.3118	0.1130	0.1689	0.5869	0.8399	0.9289
0.2271	6.0	432	0.3270	0.2611	0.3890	0.3050	0.1091	0.1608	0.5899	0.8500	0.9453
0.1905	7.0	504	0.3331	0.2651	0.3996	0.3086	0.1110	0.1645	0.5925	0.8391	0.9405
0.1436	8.0	576	0.3323	0.2648	0.4039	0.3087	0.1097	0.1653	0.6019	0.8475	0.9345
0.1687	9.0	648	0.3274	0.2620	0.3887	0.3129	0.1092	0.1622	0.5954	0.8464	0.9422
0.1407	10.0	720	0.3344	0.2689	0.4134	0.3079	0.1107	0.1667	0.6039	0.8423	0.9287
0.1159	11.0	792	0.3302	0.2675	0.4081	0.3032	0.1103	0.1646	0.6035	0.8406	0.9334
0.16	12.0	864	0.3262	0.2599	0.3989	0.2986	0.1074	0.1621	0.6177	0.8460	0.9371
0.1385	13.0	936	0.3287	0.2616	0.3976	0.3114	0.1085	0.1643	0.6095	0.8472	0.9363
0.156	14.0	1008	0.3291	0.2690	0.4147	0.3048	0.1101	0.1654	0.6082	0.8390	0.9305
0.1534	15.0	1080	0.3267	0.2651	0.3994	0.3084	0.1096	0.1632	0.6030	0.8406	0.9376
0.1196	16.0	1152	0.3248	0.2588	0.4028	0.2908	0.1065	0.1615	0.6265	0.8467	0.9357
0.0983	17.0	1224	0.3249	0.2612	0.4046	0.2940	0.1075	0.1620	0.6198	0.8440	0.9346
0.1347	18.0	1296	0.3209	0.2608	0.4012	0.2971	0.1069	0.1614	0.6201	0.8473	0.9376
0.107	19.0	1368	0.3249	0.2624	0.4026	0.3013	0.1079	0.1628	0.6149	0.8453	0.9362
0.1214	20.0	1440	0.3213	0.2586	0.3976	0.2962	0.1065	0.1609	0.6219	0.8464	0.9382
0.0921	21.0	1512	0.3240	0.2600	0.3971	0.3028	0.1074	0.1624	0.6179	0.8457	0.9383
0.0906	22.0	1584	0.3239	0.2602	0.4025	0.2968	0.1069	0.1622	0.6227	0.8461	0.9365
0.0978	23.0	1656	0.3230	0.2588	0.3990	0.2969	0.1066	0.1617	0.6234	0.8462	0.9371
0.1377	24.0	1728	0.3244	0.2612	0.4013	0.3005	0.1076	0.1626	0.6180	0.8447	0.9359
0.1253	25.0	1800	0.3242	0.2603	0.3997	0.3010	0.1073	0.1624	0.6187	0.8455	0.9378

数据统计

数据评估

sayakpaul/glpn-nyu-finetuned-diode-221214-081122浏览人数已经达到13，如你需要查询该站的相关权重信息，可以点击"5118数据""爱站数据""Chinaz数据"进入；以目前的网站数据参考，建议大家请以爱站数据为准，更多网站价值评估因素如：sayakpaul/glpn-nyu-finetuned-diode-221214-081122的访问速度、搜索引擎收录以及索引量、用户体验等；当然要评估一个站的价值，最主要还是需要根据您自身的需求以及需要，一些确切的数据则需要找sayakpaul/glpn-nyu-finetuned-diode-221214-081122的站长进行洽谈提供。如该站的IP、PV、跳出率等！

特别声明

本站OpenI提供的sayakpaul/glpn-nyu-finetuned-diode-221214-081122都来源于网络，不保证外部链接的准确性和完整性，同时，对于该外部链接的指向，不由OpenI实际控制，在2023年 5月 26日下午6:08收录时，该网页上的内容，都属于合规合法，后期网页的内容如出现违规，可以直接联系网站管理员进行删除，OpenI不承担任何责任。

OpenI致力于优质、实用的网络站点资源收集与分享！本文地址https://openi.cn/sites/10738.html转载请注明