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IAPR-TC12数据集测试结果 #22

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zhangjiwei-japan opened this issue May 29, 2024 · 3 comments
Open

IAPR-TC12数据集测试结果 #22

zhangjiwei-japan opened this issue May 29, 2024 · 3 comments

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@zhangjiwei-japan
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感谢您公开的代码,我在IAPR-TC12数据集上测试时遇到了一些问题,采用以下配置得到了Img2Txt: 0.471749 Txt2Img: 0.468014 Avg: 0.469881准确率,请问我的参数设置是否与您的有什么不同吗?谢谢
模型配置:
parser.add_argument("--data_name", type=str, default="iapr_fea", help="data name")
parser.add_argument('--root_dir', type=str, default='./')
parser.add_argument('--log_name', type=str, default='UCCH')
parser.add_argument('--pretrain', action='store_true', default=False)
parser.add_argument('--pretrain_dir', type=str, default='UCCH')
parser.add_argument('--arch', '-a', metavar='ARCH', default='vgg11', help='model architecture: ' + ' | '.join(['ResNet', 'VGG']) + ' (default: vgg11)')
parser.add_argument('--lr', type=float, default=1e-4)
parser.add_argument('--wd', type=float, default=1e-6)
parser.add_argument('--train_batch_size', type=int, default=256)
parser.add_argument('--eval_batch_size', type=int, default=256)
parser.add_argument('--max_epochs', type=int, default=100)
parser.add_argument('--log_interval', type=int, default=40)
parser.add_argument('--num_workers', type=int, default=5)
parser.add_argument('--resume', default='', type=str, metavar='PATH', help='path to latest checkpoint (default: none)')
parser.add_argument('--num_hiden_layers', default=[3, 2], nargs='+', help=' Number of hiden lyaers')
parser.add_argument('--ls', type=str, default='linear', help='lr scheduler')
parser.add_argument('--bit', type=int, default=32, help='output shape')
parser.add_argument('--optimizer', type=str, default='Adam')
parser.add_argument('--alpha', type=float, default=.9)
parser.add_argument('--momentum', type=float, default=0.4)
parser.add_argument('--K', type=int, default=4096)
parser.add_argument('--T', type=float, default=.9)
parser.add_argument('--shift', type=float, default=1)
parser.add_argument('--margin', type=float, default=.2)
parser.add_argument('--warmup_epoch', type=int, default=1)

训练与测试:
Epoch: 0 / 100
[================= 70/70 ====================>] Step: 42ms | Tot: 3s1ms | Loss: 9.875 | LR: 0.0001
Evaluation
Img2Txt: 0.451901 Txt2Img: 0.451052 Avg: 0.451476
Saving..

Epoch: 1 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s963ms | Loss: 14.796 | LR: 0.0001
Evaluation
Img2Txt: 0.453205 Txt2Img: 0.456005 Avg: 0.454605
Saving..

Epoch: 2 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s930ms | Loss: 14.545 | LR: 0.0001
Evaluation
Img2Txt: 0.458808 Txt2Img: 0.463913 Avg: 0.46136
Saving..

Epoch: 3 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s927ms | Loss: 14.429 | LR: 0.0001
Evaluation
Img2Txt: 0.457709 Txt2Img: 0.458465 Avg: 0.458087

Epoch: 4 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s925ms | Loss: 14.349 | LR: 0.0001
Evaluation
Img2Txt: 0.461355 Txt2Img: 0.462978 Avg: 0.462166
Saving..

Epoch: 5 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s930ms | Loss: 14.284 | LR: 0.0001
Evaluation
Img2Txt: 0.464578 Txt2Img: 0.464815 Avg: 0.464696
Saving..

Epoch: 6 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s920ms | Loss: 14.221 | LR: 0.0001
Evaluation
Img2Txt: 0.46529 Txt2Img: 0.466595 Avg: 0.465942
Saving..

Epoch: 7 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s925ms | Loss: 14.166 | LR: 0.0001
Evaluation
Img2Txt: 0.468146 Txt2Img: 0.467941 Avg: 0.468044
Saving..

Epoch: 8 / 100
[================= 70/70 ====================>] Step: 40ms | Tot: 2s920ms | Loss: 14.112 | LR: 0.0001
Evaluation
Img2Txt: 0.468523 Txt2Img: 0.468249 Avg: 0.468386
Saving..

Epoch: 9 / 100
[================= 70/70 ====================>] Step: 40ms | Tot: 2s921ms | Loss: 14.077 | LR: 0.0001
Evaluation
Img2Txt: 0.469653 Txt2Img: 0.469486 Avg: 0.46957
Saving..

Epoch: 10 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s929ms | Loss: 14.050 | LR: 0.0001
Evaluation
Img2Txt: 0.471134 Txt2Img: 0.470847 Avg: 0.47099
Saving..

Epoch: 11 / 100
[================= 70/70 ====================>] Step: 40ms | Tot: 2s922ms | Loss: 14.028 | LR: 0.0001
Evaluation
Img2Txt: 0.471837 Txt2Img: 0.471591 Avg: 0.471714
Saving..

Epoch: 12 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s923ms | Loss: 14.008 | LR: 0.0001
Evaluation
Img2Txt: 0.471294 Txt2Img: 0.471955 Avg: 0.471624

Epoch: 13 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s919ms | Loss: 13.994 | LR: 0.0001
Evaluation
Img2Txt: 0.472022 Txt2Img: 0.471606 Avg: 0.471814
Saving..

Epoch: 14 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s921ms | Loss: 13.984 | LR: 0.0001
Evaluation
Img2Txt: 0.471669 Txt2Img: 0.47188 Avg: 0.471775

Epoch: 15 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s924ms | Loss: 13.976 | LR: 0.0001
Evaluation
Img2Txt: 0.471544 Txt2Img: 0.471567 Avg: 0.471555

Epoch: 16 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s924ms | Loss: 13.971 | LR: 0.0001
Evaluation
Img2Txt: 0.47193 Txt2Img: 0.47138 Avg: 0.471655

Epoch: 17 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s997ms | Loss: 13.966 | LR: 0.0001
Evaluation
Img2Txt: 0.471721 Txt2Img: 0.471596 Avg: 0.471659

Epoch: 18 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s929ms | Loss: 13.963 | LR: 0.0001
Evaluation
Img2Txt: 0.472012 Txt2Img: 0.471695 Avg: 0.471854
Saving..

Epoch: 19 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s925ms | Loss: 13.960 | LR: 0.0001
Evaluation
Img2Txt: 0.472071 Txt2Img: 0.471604 Avg: 0.471838

Epoch: 20 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s927ms | Loss: 13.958 | LR: 0.0001
Evaluation
Img2Txt: 0.471887 Txt2Img: 0.471635 Avg: 0.471761

Epoch: 21 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s921ms | Loss: 13.957 | LR: 0.0001
Evaluation
Img2Txt: 0.47198 Txt2Img: 0.471801 Avg: 0.471891
Saving..

Epoch: 22 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s922ms | Loss: 13.956 | LR: 0.0001
Evaluation
Img2Txt: 0.471793 Txt2Img: 0.471491 Avg: 0.471642

Epoch: 23 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s927ms | Loss: 13.955 | LR: 0.0001
Evaluation
Img2Txt: 0.472011 Txt2Img: 0.471643 Avg: 0.471827

Epoch: 24 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s923ms | Loss: 13.954 | LR: 0.0001
Evaluation
Img2Txt: 0.471935 Txt2Img: 0.471625 Avg: 0.47178

Epoch: 25 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s924ms | Loss: 13.954 | LR: 0.0001
Evaluation
Img2Txt: 0.471816 Txt2Img: 0.471778 Avg: 0.471797

Epoch: 26 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s923ms | Loss: 13.953 | LR: 0.0001
Evaluation
Img2Txt: 0.471819 Txt2Img: 0.4716 Avg: 0.471709

Epoch: 27 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s920ms | Loss: 13.953 | LR: 0.0001
Evaluation
Img2Txt: 0.47187 Txt2Img: 0.471855 Avg: 0.471863

Epoch: 28 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s917ms | Loss: 13.953 | LR: 0.0001
Evaluation
Img2Txt: 0.471917 Txt2Img: 0.472014 Avg: 0.471966
Saving..

Epoch: 29 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s922ms | Loss: 13.952 | LR: 0.0001
Evaluation
Img2Txt: 0.471872 Txt2Img: 0.471926 Avg: 0.471899

Epoch: 30 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s928ms | Loss: 13.952 | LR: 0.0001
Evaluation
Img2Txt: 0.471692 Txt2Img: 0.471899 Avg: 0.471796

Epoch: 31 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s917ms | Loss: 13.949 | LR: 1e-05
Evaluation
Img2Txt: 0.472117 Txt2Img: 0.471916 Avg: 0.472017
Saving..

Epoch: 32 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s925ms | Loss: 13.948 | LR: 1e-05
Evaluation
Img2Txt: 0.471961 Txt2Img: 0.471928 Avg: 0.471944

Epoch: 33 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s930ms | Loss: 13.947 | LR: 1e-05
Evaluation
Img2Txt: 0.471839 Txt2Img: 0.471905 Avg: 0.471872

Epoch: 34 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s928ms | Loss: 13.947 | LR: 1e-05
Evaluation
Img2Txt: 0.471981 Txt2Img: 0.471981 Avg: 0.471981

Epoch: 35 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s928ms | Loss: 13.946 | LR: 1e-05
Evaluation
Img2Txt: 0.471843 Txt2Img: 0.471965 Avg: 0.471904

Epoch: 36 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s919ms | Loss: 13.946 | LR: 1e-05
Evaluation
Img2Txt: 0.471973 Txt2Img: 0.471943 Avg: 0.471958

Epoch: 37 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s929ms | Loss: 13.946 | LR: 1e-05
Evaluation
Img2Txt: 0.471744 Txt2Img: 0.472002 Avg: 0.471873

Epoch: 38 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s947ms | Loss: 13.946 | LR: 1e-05
Evaluation
Img2Txt: 0.471726 Txt2Img: 0.471979 Avg: 0.471852

Epoch: 39 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s925ms | Loss: 13.946 | LR: 1e-05
Evaluation
Img2Txt: 0.471826 Txt2Img: 0.471953 Avg: 0.47189

Epoch: 40 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s926ms | Loss: 13.946 | LR: 1e-05
Evaluation
Img2Txt: 0.47182 Txt2Img: 0.471969 Avg: 0.471894

Epoch: 41 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s917ms | Loss: 13.946 | LR: 1e-05
Evaluation
Img2Txt: 0.471834 Txt2Img: 0.471982 Avg: 0.471908

Epoch: 42 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s923ms | Loss: 13.946 | LR: 1e-05
Evaluation
Img2Txt: 0.471956 Txt2Img: 0.471948 Avg: 0.471952

Epoch: 43 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s924ms | Loss: 13.946 | LR: 1e-05
Evaluation
Img2Txt: 0.471862 Txt2Img: 0.471979 Avg: 0.471921

Epoch: 44 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s928ms | Loss: 13.946 | LR: 1e-05
Evaluation
Img2Txt: 0.47187 Txt2Img: 0.471959 Avg: 0.471915

Epoch: 45 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s926ms | Loss: 13.946 | LR: 1e-05
Evaluation
Img2Txt: 0.471792 Txt2Img: 0.471953 Avg: 0.471873

Epoch: 46 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s926ms | Loss: 13.945 | LR: 1e-05
Evaluation
Img2Txt: 0.471685 Txt2Img: 0.472025 Avg: 0.471855

Epoch: 47 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s926ms | Loss: 13.945 | LR: 1e-05
Evaluation
Img2Txt: 0.471827 Txt2Img: 0.472015 Avg: 0.471921

Epoch: 48 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s928ms | Loss: 13.946 | LR: 1e-05
Evaluation
Img2Txt: 0.472013 Txt2Img: 0.471981 Avg: 0.471997

Epoch: 49 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s922ms | Loss: 13.946 | LR: 1e-05
Evaluation
Img2Txt: 0.471937 Txt2Img: 0.471982 Avg: 0.471959

Epoch: 50 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s919ms | Loss: 13.945 | LR: 1e-05
Evaluation
Img2Txt: 0.471814 Txt2Img: 0.471958 Avg: 0.471886

Epoch: 51 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s921ms | Loss: 13.946 | LR: 1e-05
Evaluation
Img2Txt: 0.471996 Txt2Img: 0.471978 Avg: 0.471987

Epoch: 52 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s920ms | Loss: 13.945 | LR: 1e-05
Evaluation
Img2Txt: 0.471771 Txt2Img: 0.471981 Avg: 0.471876

Epoch: 53 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s927ms | Loss: 13.945 | LR: 1e-05
Evaluation
Img2Txt: 0.47176 Txt2Img: 0.471986 Avg: 0.471873

Epoch: 54 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s922ms | Loss: 13.945 | LR: 1e-05
Evaluation
Img2Txt: 0.471765 Txt2Img: 0.47202 Avg: 0.471892

Epoch: 55 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s921ms | Loss: 13.945 | LR: 1e-05
Evaluation
Img2Txt: 0.471874 Txt2Img: 0.472009 Avg: 0.471942

Epoch: 56 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s918ms | Loss: 13.945 | LR: 1e-05
Evaluation
Img2Txt: 0.471936 Txt2Img: 0.47193 Avg: 0.471933

Epoch: 57 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s931ms | Loss: 13.945 | LR: 1e-05
Evaluation
Img2Txt: 0.472061 Txt2Img: 0.472083 Avg: 0.472072
Saving..

Epoch: 58 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s918ms | Loss: 13.945 | LR: 1e-05
Evaluation
Img2Txt: 0.471972 Txt2Img: 0.47204 Avg: 0.472006

Epoch: 59 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s920ms | Loss: 13.945 | LR: 1e-05
Evaluation
Img2Txt: 0.471962 Txt2Img: 0.472009 Avg: 0.471986

Epoch: 60 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s924ms | Loss: 13.945 | LR: 1e-05
Evaluation
Img2Txt: 0.472024 Txt2Img: 0.472021 Avg: 0.472023

Epoch: 61 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s918ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472109 Txt2Img: 0.472094 Avg: 0.472102
Saving..

Epoch: 62 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s927ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472083 Txt2Img: 0.472026 Avg: 0.472055

Epoch: 63 / 100
[================= 70/70 ====================>] Step: 40ms | Tot: 2s919ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472093 Txt2Img: 0.472024 Avg: 0.472058

Epoch: 64 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s924ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472098 Txt2Img: 0.472027 Avg: 0.472063

Epoch: 65 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s923ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472026 Txt2Img: 0.472036 Avg: 0.472031

Epoch: 66 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s914ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472026 Txt2Img: 0.472036 Avg: 0.472031

Epoch: 67 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s923ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.47203 Txt2Img: 0.472037 Avg: 0.472034

Epoch: 68 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s922ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472082 Txt2Img: 0.472032 Avg: 0.472057

Epoch: 69 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s926ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472035 Txt2Img: 0.472033 Avg: 0.472034

Epoch: 70 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s922ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472031 Txt2Img: 0.47203 Avg: 0.472031

Epoch: 71 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s916ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472021 Txt2Img: 0.472034 Avg: 0.472028

Epoch: 72 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s920ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472082 Txt2Img: 0.472032 Avg: 0.472057

Epoch: 73 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s921ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.47202 Txt2Img: 0.472036 Avg: 0.472028

Epoch: 74 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s927ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.471985 Txt2Img: 0.472042 Avg: 0.472014

Epoch: 75 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s920ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472083 Txt2Img: 0.472036 Avg: 0.472059

Epoch: 76 / 100
[================= 70/70 ====================>] Step: 40ms | Tot: 2s921ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472059 Txt2Img: 0.472036 Avg: 0.472047

Epoch: 77 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s925ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472077 Txt2Img: 0.472035 Avg: 0.472056

Epoch: 78 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s924ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.471933 Txt2Img: 0.472049 Avg: 0.471991

Epoch: 79 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s923ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.471957 Txt2Img: 0.472032 Avg: 0.471995

Epoch: 80 / 100
[================= 70/70 ====================>] Step: 42ms | Tot: 2s928ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.471867 Txt2Img: 0.472035 Avg: 0.471951

Epoch: 81 / 100
[================= 70/70 ====================>] Step: 40ms | Tot: 2s912ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.471913 Txt2Img: 0.472049 Avg: 0.471981

Epoch: 82 / 100
[================= 70/70 ====================>] Step: 40ms | Tot: 2s924ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472036 Txt2Img: 0.472042 Avg: 0.472039

Epoch: 83 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s919ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.471955 Txt2Img: 0.471997 Avg: 0.471976

Epoch: 84 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s917ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472018 Txt2Img: 0.472045 Avg: 0.472032

Epoch: 85 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s927ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.471952 Txt2Img: 0.472043 Avg: 0.471997

Epoch: 86 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s925ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472036 Txt2Img: 0.472035 Avg: 0.472036

Epoch: 87 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s921ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.47198 Txt2Img: 0.472041 Avg: 0.472011

Epoch: 88 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s927ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.472054 Txt2Img: 0.472003 Avg: 0.472028

Epoch: 89 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s926ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.471952 Txt2Img: 0.472043 Avg: 0.471997

Epoch: 90 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s918ms | Loss: 13.945 | LR: 1e-06
Evaluation
Img2Txt: 0.471952 Txt2Img: 0.472043 Avg: 0.471997

Epoch: 91 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s921ms | Loss: 13.945 | LR: 1e-07
Evaluation
Img2Txt: 0.471952 Txt2Img: 0.472043 Avg: 0.471997

Epoch: 92 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s925ms | Loss: 13.945 | LR: 1e-07
Evaluation
Img2Txt: 0.471952 Txt2Img: 0.472043 Avg: 0.471997

Epoch: 93 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s932ms | Loss: 13.945 | LR: 1e-07
Evaluation
Img2Txt: 0.471952 Txt2Img: 0.472043 Avg: 0.471997

Epoch: 94 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s930ms | Loss: 13.945 | LR: 1e-07
Evaluation
Img2Txt: 0.471952 Txt2Img: 0.472043 Avg: 0.471997

Epoch: 95 / 100
[================= 70/70 ====================>] Step: 42ms | Tot: 2s920ms | Loss: 13.945 | LR: 1e-07
Evaluation
Img2Txt: 0.471952 Txt2Img: 0.472043 Avg: 0.471997

Epoch: 96 / 100
[================= 70/70 ====================>] Step: 40ms | Tot: 2s917ms | Loss: 13.945 | LR: 1e-07
Evaluation
Img2Txt: 0.471952 Txt2Img: 0.472043 Avg: 0.471997

Epoch: 97 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s926ms | Loss: 13.945 | LR: 1e-07
Evaluation
Img2Txt: 0.471952 Txt2Img: 0.472043 Avg: 0.471997

Epoch: 98 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s915ms | Loss: 13.945 | LR: 1e-07
Evaluation
Img2Txt: 0.471952 Txt2Img: 0.472043 Avg: 0.471997

Epoch: 99 / 100
[================= 70/70 ====================>] Step: 41ms | Tot: 2s928ms | Loss: 13.945 | LR: 1e-07
Evaluation
Img2Txt: 0.471952 Txt2Img: 0.472043 Avg: 0.471997
Test
Img2Txt: 0.471749 Txt2Img: 0.468014 Avg: 0.469881

@penghu-cs
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penghu-cs commented May 29, 2024 via email

@zhangjiwei-japan
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不是的,我使用的是特征提取后的数据集“iapr-tc12-rand.mat”

@penghu-cs
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您可以试试如下的参数:python UCCH.py --data_name iapr_fea --num_hiden_layers 4 3 --max_epochs 100 --train_batch_size 256 --lr 0.0001 --optimizer Adam --shift 3 --alpha 0.4 --margin 0.1 --bit 32

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