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add IP addresses idenfiter with fine-tuned models

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This commit is contained in:
Frank Xu
2023-08-20 09:01:30 -04:00
parent 666df5a517
commit 28056bcb65
5 changed files with 1168 additions and 1 deletions
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AI4Forensics/IP_Identifier_Fine_Tuning/IP_Identifer_Fine_Tuning.pptx
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623,29567,623,0.002411996990649641,1.0,1.0,,,,,,,,,
624,29592,624,0.003964523364211344,1.0,1.0,,,,,,,,,
625,29681,625,0.0030841385877267225,1.0,1.0,0.027998152176969146,1.0,1.0,,,,,,
626,29722,626,0.002293454506116632,1.0,1.0,,,,,,,,,
627,29763,627,0.005469170892400826,1.0,1.0,,,,,,,,,
628,29804,628,0.002298949975292544,1.0,1.0,,,,,,,,,
629,29845,629,0.0034687674441392746,1.0,1.0,,,,,,,,,
630,29878,630,0.002530964562582483,1.0,1.0,,,,,,,,,
631,29911,631,0.004269581710612016,1.0,1.0,,,,,,,,,
632,29952,632,0.005287030302905578,1.0,1.0,,,,,,,,,
633,29985,633,0.0033607394386157806,1.0,1.0,0.0026687447445783623,1.0,1.0,,,,,,
634,30010,634,0.0014693371871582408,1.0,1.0,,,,,,,,,
635,30043,635,0.0031539440315046367,1.0,1.0,,,,,,,,,
636,30076,636,0.0030359581355645557,1.0,1.0,,,,,,,,,
637,30101,637,0.0014814399549914015,1.0,1.0,,,,,,,,,
638,30142,638,0.0038873985496336444,1.0,1.0,,,,,,,,,
639,30175,639,0.0024085507500024054,1.0,1.0,,,,,,,,,
640,30208,640,0.0021334698368809767,1.0,1.0,,,,,,,,,
641,30249,641,0.003652064207110925,1.0,1.0,0.006725433730568967,1.0,1.0,,,,,,
642,30314,642,0.03416673927120598,0.0,0.0,,,,,,,,,
643,30355,643,0.004086532553790122,1.0,1.0,,,,,,,,,
644,30388,644,0.002299366494357855,1.0,1.0,,,,,,,,,
645,30413,645,0.0017982698780302068,1.0,1.0,,,,,,,,,
646,30438,646,0.0018251007819048938,1.0,1.0,,,,,,,,,
647,30471,647,0.0036919359401849762,1.0,1.0,,,,,,,,,
648,30496,648,0.00561342578629592,1.0,1.0,,,,,,,,,
649,30585,649,0.0025224411052725128,1.0,1.0,0.002001723699677314,1.0,1.0,,,,,,
650,30610,650,0.0014361863520245303,1.0,1.0,,,,,,,,,
651,30643,651,0.006170663640339171,1.0,1.0,,,,,,,,,
652,30684,652,0.004581734099439473,1.0,1.0,,,,,,,,,
653,30709,653,0.002163913224113306,1.0,1.0,,,,,,,,,
654,30750,654,0.0033945433870435416,1.0,1.0,,,,,,,,,
655,30775,655,0.002131028260448223,1.0,1.0,,,,,,,,,
656,30808,656,0.0037039272214381925,1.0,1.0,,,,,,,,,
657,30833,657,0.001974822690259259,1.0,1.0,0.0028021581104828784,1.0,1.0,,,,,,
658,30866,658,0.002156632485144314,1.0,1.0,,,,,,,,,
659,30891,659,0.0017080097990033968,1.0,1.0,,,,,,,,,
660,31012,660,0.038177843334056896,1.0,1.0,,,,,,,,,
661,31077,661,0.002747984222459224,1.0,1.0,,,,,,,,,
662,31166,662,0.0023493104742224923,1.0,1.0,,,,,,,,,
663,31191,663,0.008487881945835244,1.0,1.0,,,,,,,,,
664,31304,664,0.04231206878254235,1.0,1.0,,,,,,,,,
665,31361,665,0.015215694230513626,1.0,1.0,0.0013837619587805724,1.0,1.0,,,,,,
666,31490,666,0.03591513582745535,1.0,1.0,,,,,,,,,
667,31531,667,0.005085019459517483,1.0,1.0,,,,,,,,,
668,31556,668,0.001795864781023132,1.0,1.0,,,,,,,,,
669,31677,669,0.038666528565079405,1.0,1.0,,,,,,,,,
670,31710,670,0.0021584980261866345,1.0,1.0,,,,,,,,,
671,31743,671,0.008085111600470523,1.0,1.0,,,,,,,,,
672,31776,672,0.004535103148454738,1.0,1.0,,,,,,,,,
673,31809,673,0.0058906742437295646,1.0,1.0,0.006498069727926179,1.0,1.0,,,,,,
674,31834,674,0.001827985430524753,1.0,1.0,,,,,,,,,
675,31875,675,0.00364233891494115,1.0,1.0,,,,,,,,,
676,31900,676,0.001931552588011319,1.0,1.0,,,,,,,,,
677,32029,677,0.036205323013049476,1.0,1.0,,,,,,,,,
678,32054,678,0.0013846837102050812,1.0,1.0,,,,,,,,,
679,32095,679,0.0043542447196439306,1.0,1.0,,,,,,,,,
680,32120,680,0.00577771863262645,1.0,1.0,,,,,,,,,
681,32145,681,0.003957892355567859,1.0,1.0,0.021329540312391832,1.0,1.0,,,,,,
682,32186,682,0.0029775799205433353,1.0,1.0,,,,,,,,,
683,32259,683,0.027764181659045383,1.0,1.0,,,,,,,,,
684,32292,684,0.009632070107329582,1.0,1.0,,,,,,,,,
685,32317,685,0.001913364828647085,1.0,1.0,,,,,,,,,
686,32350,686,0.008256996994122261,1.0,1.0,,,,,,,,,
687,32439,687,0.002696479044664722,1.0,1.0,,,,,,,,,
688,32480,688,0.011437369231234697,1.0,1.0,,,,,,,,,
689,32521,689,0.004123384450207596,1.0,1.0,0.0013611759538904758,1.0,1.0,,,,,,
690,32554,690,0.021328601403353388,1.0,1.0,,,,,,,,,
691,32579,691,0.0019112908669925825,1.0,1.0,,,,,,,,,
692,32612,692,0.0020984052778896967,1.0,1.0,,,,,,,,,
693,32653,693,0.003886208962380579,1.0,1.0,,,,,,,,,
694,32734,694,0.02024900971205125,1.0,1.0,,,,,,,,,
695,32775,695,0.004149458056376716,1.0,1.0,,,,,,,,,
696,32800,696,0.007904861976567947,1.0,1.0,,,,,,,,,
697,32833,697,0.0030053626542559182,1.0,1.0,0.014331867724937788,1.0,1.0,,,,,,
698,32954,698,0.03846804843888004,1.0,1.0,,,,,,,,,
699,32987,699,0.004124619444397126,1.0,1.0,,,,,,,,,
700,33012,700,0.004192819879951155,1.0,1.0,,,,,,,,,
701,33037,701,0.005743955528466434,1.0,1.0,,,,,,,,,
702,33078,702,0.001999935150157285,1.0,1.0,,,,,,,,,
703,33111,703,0.008503282630630622,1.0,1.0,,,,,,,,,
704,33152,704,0.0037001522724915085,1.0,1.0,,,,,,,,,
705,33177,705,0.003087129954659531,1.0,1.0,0.012496777327306747,1.0,1.0,,,,,,
706,33210,706,0.00350194301292305,1.0,1.0,,,,,,,,,
707,33235,707,0.014080687296673014,1.0,1.0,,,,,,,,,
708,33276,708,0.00410933899247948,1.0,1.0,,,,,,,,,
709,33397,709,0.037851613223152565,1.0,1.0,,,,,,,,,
710,33510,710,0.040810033148644446,1.0,1.0,,,,,,,,,
711,33551,711,0.002418716375742591,1.0,1.0,,,,,,,,,
712,33592,712,0.003624795394367439,1.0,1.0,,,,,,,,,
713,33633,713,0.0037505140744567597,1.0,1.0,0.014227452131376592,1.0,1.0,,,,,,
714,33666,714,0.002089423445002012,1.0,1.0,,,,,,,,,
715,33771,715,0.025000065846041846,1.0,1.0,,,,,,,,,
716,33812,716,0.004941091954005515,1.0,1.0,,,,,,,,,
717,33845,717,0.0027349276239888812,1.0,1.0,,,,,,,,,
718,33886,718,0.005136407480595339,1.0,1.0,,,,,,,,,
719,33919,719,0.0019504698773107519,1.0,1.0,,,,,,,,,
720,33952,720,0.0019459015358324907,1.0,1.0,,,,,,,,,
721,33993,721,0.00907403369688086,1.0,1.0,0.003248707907472029,1.0,1.0,,,,,,
722,34018,722,0.0018039287319637268,1.0,1.0,,,,,,,,,
723,34043,723,0.0038322164314018884,1.0,1.0,,,,,,,,,
724,34108,724,0.0026914926717658714,1.0,1.0,,,,,,,,,
725,34229,725,0.038918225287749464,1.0,1.0,,,,,,,,,
726,34270,726,0.0032807265786382236,1.0,1.0,,,,,,,,,
727,34383,727,0.04014369331250983,1.0,1.0,,,,,,,,,
728,34424,728,0.0024898565655033598,1.0,1.0,,,,,,,,,
729,34457,729,0.0020895211450579153,1.0,1.0,0.0018949493887492016,1.0,1.0,,,,,,
730,34570,730,0.04094184044472123,1.0,1.0,,,,,,,,,
731,34595,731,0.004170812957869808,1.0,1.0,,,,,,,,,
732,34620,732,0.002500022928001897,1.0,1.0,,,,,,,,,
733,34661,733,0.0037272271053777786,1.0,1.0,,,,0.97826087474823,0.9714285714285714,1.0,0.9975490196078431,0.999147305981216,0.9855072463768115
1 step elapsed_tokens elapsed_examples training_loss training_sequence_accuracy training_token_accuracy validation_loss validation_sequence_accuracy validation_token_accuracy classification/accuracy classification/precision classification/recall classification/auroc classification/auprc classification/f1.0
2 1 41 1 0.36131611532358515 0.0 0.0 0.4872071744380082 0.0 0.0
3 2 74 2 0.3700738534195625 0.0 0.0
4 3 107 3 0.22843073428540267 0.0 0.0
5 4 148 4 0.18925983548845396 0.0 0.0
6 5 173 5 0.06851752833268013 1.0 1.0
7 6 262 6 0.02713874108659432 1.0 1.0
8 7 375 7 0.05557006998931683 1.0 1.0
9 8 416 8 0.037689568018540745 1.0 1.0
10 9 441 9 0.03327601474069525 1.0 1.0 0.031220039141662707 1.0 1.0
11 10 506 10 0.031220039141662707 1.0 1.0
12 11 539 11 0.22557505111595672 0.0 0.0
13 12 620 12 0.0694835970180284 0.0 0.0
14 13 661 13 0.0693355020871386 0.0 0.0
15 14 694 14 0.045931317708786994 0.0 0.0
16 15 735 15 0.028463621933449756 1.0 1.0
17 16 760 16 0.020192973992889166 1.0 1.0
18 17 785 17 0.017002813986327962 1.0 1.0 0.028524243063839095 1.0 1.0
19 18 874 18 0.026500673530919647 1.0 1.0
20 19 899 19 0.022513926106815536 1.0 1.0
21 20 1020 20 0.05054291217876016 1.0 1.0
22 21 1053 21 0.17471788834329344 0.0 0.0
23 22 1094 22 0.02836188224214129 1.0 1.0
24 23 1135 23 0.034800293915439394 1.0 1.0
25 24 1248 24 0.0544320389855836 1.0 1.0
26 25 1281 25 0.03246741641443805 1.0 1.0 0.032951377297674 1.0 1.0
27 26 1322 26 0.03000724712666124 1.0 1.0
28 27 1347 27 0.021077466012599567 1.0 1.0
29 28 1372 28 0.02064567490713671 1.0 1.0
30 29 1437 29 0.05725409627833869 0.0 0.0
31 30 1470 30 0.016648737896612146 1.0 1.0
32 31 1495 31 0.14679759012768046 0.0 0.0
33 32 1528 32 0.020843235227948755 1.0 1.0
34 33 1561 33 0.03276810964700416 1.0 1.0 0.04024752794350206 0.0 0.0
35 34 1626 34 0.040496221549910845 0.0 0.0
36 35 1651 35 0.04781833109387662 0.0 0.0
37 36 1684 36 0.030358177107700612 1.0 1.0
38 37 1717 37 0.031779489604959965 1.0 1.0
39 38 1830 38 0.051204410766845926 1.0 1.0
40 39 1855 39 0.012860343157080935 1.0 1.0
41 40 1880 40 0.014500696788697193 1.0 1.0
42 41 1913 41 0.013097912614466625 1.0 1.0 0.01010702661355026 1.0 1.0
43 42 1954 42 0.017973546807654204 1.0 1.0
44 43 1987 43 0.012875115118658869 1.0 1.0
45 44 2012 44 0.008627477259433362 1.0 1.0
46 45 2125 45 0.050168912711680086 1.0 1.0
47 46 2166 46 0.026348685119068252 1.0 1.0
48 47 2207 47 0.018747832050081344 1.0 1.0
49 48 2248 48 0.02532638164306991 1.0 1.0
50 49 2289 49 0.016451444947510028 1.0 1.0 0.2877718317729523 0.0 0.0
51 50 2330 50 0.02226830317033455 1.0 1.0
52 51 2363 51 0.3006473934961832 0.0 0.0
53 52 2396 52 0.00395260537712602 1.0 1.0
54 53 2461 53 0.02284509134817199 1.0 1.0
55 54 2542 54 0.026175346902920865 1.0 1.0
56 55 2567 55 0.010952326249098403 1.0 1.0
57 56 2592 56 0.014134095167488947 1.0 1.0
58 57 2697 57 0.028973295194849088 1.0 1.0 0.01551858661980077 1.0 1.0
59 58 2722 58 0.014299217964702012 1.0 1.0
60 59 2747 59 0.00834741592252006 1.0 1.0
61 60 2788 60 0.02308588253887138 1.0 1.0
62 61 2813 61 0.00906841204026326 1.0 1.0
63 62 2934 62 0.046945270747467786 1.0 1.0
64 63 2975 63 0.022567503625876274 1.0 1.0
65 64 3008 64 0.007562187540606828 1.0 1.0
66 65 3041 65 0.007075891750610026 1.0 1.0 0.11367509979154419 0.0 0.0
67 66 3106 66 0.026230665613984454 1.0 1.0
68 67 3147 67 0.020585892829170917 1.0 1.0
69 68 3172 68 0.007856541990040567 1.0 1.0
70 69 3213 69 0.020074003617279235 1.0 1.0
71 70 3334 70 0.0462450483632371 1.0 1.0
72 71 3359 71 0.007845374103732561 1.0 1.0
73 72 3400 72 0.01965699916551239 1.0 1.0
74 73 3441 73 0.018607642447226683 1.0 1.0 0.00570118249716567 1.0 1.0
75 74 3474 74 0.00448214579580963 1.0 1.0
76 75 3539 75 0.020936313641382185 1.0 1.0
77 76 3572 76 0.1889746366855661 0.0 0.0
78 77 3613 77 0.017631995898351304 1.0 1.0
79 78 3654 78 0.015714159191644286 1.0 1.0
80 79 3679 79 0.008651148353856115 1.0 1.0
81 80 3720 80 0.020361671341634066 1.0 1.0
82 81 3785 81 0.022455738474429835 1.0 1.0 0.022708754392936042 1.0 1.0
83 82 3826 82 0.022248722614873262 1.0 1.0
84 83 3867 83 0.016634664889323178 1.0 1.0
85 84 3892 84 0.015879148010002002 1.0 1.0
86 85 3981 85 0.02129320362886078 1.0 1.0
87 86 4022 86 0.013185540407779629 1.0 1.0
88 87 4055 87 0.010587486446347612 1.0 1.0
89 88 4080 88 0.02218080692789954 1.0 1.0
90 89 4121 89 0.016163602579075814 1.0 1.0 0.018447448047036234 1.0 1.0
91 90 4210 90 0.018967157456083277 1.0 1.0
92 91 4243 91 0.003596439868570087 1.0 1.0
93 92 4316 92 0.10245768553965415 0.0 0.0
94 93 4357 93 0.020223705363583578 1.0 1.0
95 94 4390 94 0.008596739505919687 1.0 1.0
96 95 4415 95 0.0059946262955782 1.0 1.0
97 96 4448 96 0.02165651834432538 1.0 1.0
98 97 4473 97 0.006453505932343735 1.0 1.0 0.004207050470713512 1.0 1.0
99 98 4594 98 0.046886877945600036 1.0 1.0
100 99 4627 99 0.11959624585262645 0.0 0.0
101 100 4652 100 0.009025092869123908 1.0 1.0
102 101 4677 101 0.01159204928218969 1.0 1.0
103 102 4718 102 0.021466303803201303 1.0 1.0
104 103 4743 103 0.024004962817707566 1.0 1.0
105 104 4816 104 0.04579475395743631 0.0 0.0
106 105 4849 105 0.018203865305422368 1.0 1.0 0.04196793750077632 0.0 0.0
107 106 4890 106 0.017205431483860594 1.0 1.0
108 107 4923 107 0.023016606093224257 1.0 1.0
109 108 4996 108 0.03363417840498894 1.0 1.0
110 109 5029 109 0.01055616332631871 1.0 1.0
111 110 5070 110 0.010952473264303991 1.0 1.0
112 111 5095 111 0.008982319584368573 1.0 1.0
113 112 5120 112 0.00998764863734929 1.0 1.0
114 113 5145 113 0.0102364023392632 1.0 1.0 0.1434572506475815 0.0 0.0
115 114 5186 114 0.010304133885405464 1.0 1.0
116 115 5219 115 0.007398418430739184 1.0 1.0
117 116 5252 116 0.160425701745653 0.0 0.0
118 117 5341 117 0.01727596476598013 1.0 1.0
119 118 5366 118 0.0039912293913948816 1.0 1.0
120 119 5407 119 0.01271170173792052 1.0 1.0
121 120 5520 120 0.04855149958462009 1.0 1.0
122 121 5553 121 0.016561159628035966 1.0 1.0 0.07796625686372863 0.0 0.0
123 122 5586 122 0.03658135385616333 1.0 1.0
124 123 5627 123 0.010930833159567555 1.0 1.0
125 124 5668 124 0.011949884182671667 1.0 1.0
126 125 5701 125 0.016956832591095008 1.0 1.0
127 126 5726 126 0.022571875492479496 1.0 1.0
128 127 5759 127 0.012888053933593255 1.0 1.0
129 128 5792 128 0.005133158288572304 1.0 1.0
130 129 5881 129 0.01916009849995052 1.0 1.0 0.013847733811394394 1.0 1.0
131 130 5906 130 0.012011411931428788 1.0 1.0
132 131 5931 131 0.007971257554709154 1.0 1.0
133 132 5964 132 0.08846963041842174 0.0 0.0
134 133 6189 133 0.033074644572998295 1.0 1.0
135 134 6310 134 0.04549703621705217 1.0 1.0
136 135 6343 135 0.009617989432827016 1.0 1.0
137 136 6384 136 0.014371102429315217 1.0 1.0
138 137 6417 137 0.014548937769359328 1.0 1.0 0.00995008055856791 1.0 1.0
139 138 6538 138 0.04630857212240517 1.0 1.0
140 139 6667 139 0.04324543540203195 1.0 1.0
141 140 6708 140 0.010653898217366078 1.0 1.0
142 141 6733 141 0.006511889914133159 1.0 1.0
143 142 6774 142 0.011161583856330252 1.0 1.0
144 143 6807 143 0.012623354419356475 1.0 1.0
145 144 6856 144 0.02774330338124855 1.0 1.0
146 145 6945 145 0.017150625479364613 1.0 1.0 0.016266316846322296 1.0 1.0
147 146 6994 146 0.023999675555041906 1.0 1.0
148 147 7035 147 0.01443589308463561 1.0 1.0
149 148 7124 148 0.01593858884255083 1.0 1.0
150 149 7157 149 0.0039451327360802676 1.0 1.0
151 150 7286 150 0.041224458131234765 1.0 1.0
152 151 7327 151 0.008721806495872442 1.0 1.0
153 152 7360 152 0.003449108358909143 1.0 1.0
154 153 7441 153 0.031120321435428196 1.0 1.0 0.011828955701554756 1.0 1.0
155 154 7482 154 0.009850116068482748 1.0 1.0
156 155 7515 155 0.01212568152328231 1.0 1.0
157 156 7540 156 0.009057329903413725 1.0 1.0
158 157 7573 157 0.008076899820198376 1.0 1.0
159 158 7598 158 0.00785573707279582 1.0 1.0
160 159 7623 159 0.0109080523573175 1.0 1.0
161 160 7680 160 0.01987976644248452 1.0 1.0
162 161 7705 161 0.010745363941047492 1.0 1.0 0.010937099401571686 1.0 1.0
163 162 7730 162 0.30798120539652396 0.0 0.0
164 163 7763 163 0.00899759478130818 1.0 1.0
165 164 7804 164 0.01044557543134579 1.0 1.0
166 165 7837 165 0.03216896385778455 1.0 1.0
167 166 7902 166 0.025793771446051328 1.0 1.0
168 167 7927 167 0.016294540036627343 1.0 1.0
169 168 7952 168 0.01383792414747101 1.0 1.0
170 169 8073 169 0.0442201690788764 1.0 1.0 0.019650482941906376 1.0 1.0
171 170 8114 170 0.010494683315548172 1.0 1.0
172 171 8155 171 0.021872556327361962 1.0 1.0
173 172 8188 172 0.010315648031782984 1.0 1.0
174 173 8253 173 0.09507020872195425 0.0 0.0
175 174 8350 174 0.03518366060497404 1.0 1.0
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README.md
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## Table of Contents (Add the draft (in progress): AI for Forensics - Identifying IPs with a Fine-tuned Model, 8/2023)
## Table of Contents (Added: AI for Forensics - Identifying IPs with a Fine-tuned Model, 8/2023)
- Basic Computer Skills for Digital Forensics