data_file2.txt

Searching for incumbent config!
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.001

Epoch: 0. Loss: 0.2891264259815216. Accuracy: 80
Epoch: 1. Loss: 0.2681436836719513. Accuracy: 84
Epoch: 2. Loss: 0.22425276041030884. Accuracy: 86
Epoch: 3. Loss: 0.12473046034574509. Accuracy: 87
Epoch: 4. Loss: 0.047873955219984055. Accuracy: 89
Epoch: 5. Loss: 0.12005382776260376. Accuracy: 89
Epoch: 6. Loss: 0.07660261541604996. Accuracy: 90
Epoch: 7. Loss: 0.10061220079660416. Accuracy: 90
Epoch: 8. Loss: 0.08886595815420151. Accuracy: 90
Epoch: 9. Loss: 0.05263439193367958. Accuracy: 91
Epoch: 10. Loss: 0.0485222153365612. Accuracy: 90
Epoch: 11. Loss: 0.07375369220972061. Accuracy: 91
Epoch: 12. Loss: 0.020627358928322792. Accuracy: 91
Epoch: 13. Loss: 0.053971365094184875. Accuracy: 91
Epoch: 14. Loss: 0.05043112114071846. Accuracy: 91
[ 0.001 128 tensor(91) ]
Loss: 0.05043112114071846
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.028335396973329874

Epoch: 0. Loss: 0.34055793285369873. Accuracy: 76
Epoch: 1. Loss: 0.47504523396492004. Accuracy: 76
Epoch: 2. Loss: 0.2870958149433136. Accuracy: 79
Epoch: 3. Loss: 0.404972106218338. Accuracy: 80
Epoch: 4. Loss: 0.3723088204860687. Accuracy: 77
Epoch: 5. Loss: 0.4216432571411133. Accuracy: 78
Epoch: 6. Loss: 0.3563448190689087. Accuracy: 78
Epoch: 7. Loss: 0.37977662682533264. Accuracy: 76
Epoch: 8. Loss: 0.2195575088262558. Accuracy: 77
Epoch: 9. Loss: 0.3592621386051178. Accuracy: 79
Epoch: 10. Loss: 0.4861237108707428. Accuracy: 78
Epoch: 11. Loss: 0.2810356318950653. Accuracy: 77
Epoch: 12. Loss: 0.4049622714519501. Accuracy: 78
Epoch: 13. Loss: 0.5860717296600342. Accuracy: 79
Epoch: 14. Loss: 0.20357728004455566. Accuracy: 80
[ 0.028335396973329874 128 tensor(80) ]
Loss: 0.20357728004455566
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.01187615930744871

Epoch: 0. Loss: 0.224986270070076. Accuracy: 83
Epoch: 1. Loss: 0.3111792802810669. Accuracy: 83
Epoch: 2. Loss: 0.15817835927009583. Accuracy: 84
Epoch: 3. Loss: 0.2548060119152069. Accuracy: 83
Epoch: 4. Loss: 0.33529651165008545. Accuracy: 84
Epoch: 5. Loss: 0.16754522919654846. Accuracy: 85
Epoch: 6. Loss: 0.16660651564598083. Accuracy: 85
Epoch: 7. Loss: 0.2307066172361374. Accuracy: 85
Epoch: 8. Loss: 0.15300564467906952. Accuracy: 85
Epoch: 9. Loss: 0.12764404714107513. Accuracy: 85
Epoch: 10. Loss: 0.10438057780265808. Accuracy: 85
Epoch: 11. Loss: 0.20051059126853943. Accuracy: 84
Epoch: 12. Loss: 0.19074632227420807. Accuracy: 86
Epoch: 13. Loss: 0.023665040731430054. Accuracy: 86
Epoch: 14. Loss: 0.09178237617015839. Accuracy: 86
[ 0.01187615930744871 32 tensor(86) ]
Loss: 0.09178237617015839
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.025437628994347983

Epoch: 0. Loss: 0.6503061652183533. Accuracy: 68
Epoch: 1. Loss: 0.45515894889831543. Accuracy: 70
Epoch: 2. Loss: 0.4838297665119171. Accuracy: 69
Epoch: 3. Loss: 0.5174617767333984. Accuracy: 71
Epoch: 4. Loss: 0.4386899471282959. Accuracy: 70
Epoch: 5. Loss: 0.40595874190330505. Accuracy: 71
Epoch: 6. Loss: 0.7038387656211853. Accuracy: 71
Epoch: 7. Loss: 0.4906952679157257. Accuracy: 71
Epoch: 8. Loss: 0.4222659766674042. Accuracy: 72
Epoch: 9. Loss: 0.4992126524448395. Accuracy: 73
Epoch: 10. Loss: 0.42082223296165466. Accuracy: 74
Epoch: 11. Loss: 0.37280070781707764. Accuracy: 76
Epoch: 12. Loss: 0.3005296289920807. Accuracy: 76
Epoch: 13. Loss: 0.39127716422080994. Accuracy: 77
Epoch: 14. Loss: 0.3234308660030365. Accuracy: 79
[ 0.025437628994347983 128 tensor(79) ]
Loss: 0.3234308660030365
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.0750817570997284

Epoch: 0. Loss: 2.3080248832702637. Accuracy: 10
Epoch: 1. Loss: 2.3495607376098633. Accuracy: 10
Epoch: 2. Loss: 2.315317392349243. Accuracy: 10
Epoch: 3. Loss: 2.3039045333862305. Accuracy: 10
Epoch: 4. Loss: 2.287003993988037. Accuracy: 10
Epoch: 5. Loss: 2.3451366424560547. Accuracy: 10
Epoch: 6. Loss: 2.3074746131896973. Accuracy: 10
Epoch: 7. Loss: 2.311126232147217. Accuracy: 10
Epoch: 8. Loss: 2.3061208724975586. Accuracy: 10
Epoch: 9. Loss: 2.3093209266662598. Accuracy: 10
Epoch: 10. Loss: 2.336181640625. Accuracy: 10
Epoch: 11. Loss: 2.3240408897399902. Accuracy: 10
Epoch: 12. Loss: 2.272634744644165. Accuracy: 10
Epoch: 13. Loss: 2.2857844829559326. Accuracy: 10
Epoch: 14. Loss: 2.3011181354522705. Accuracy: 10
[ 0.0750817570997284 64 tensor(10) ]
Loss: 2.3011181354522705
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.060040727520174746

Epoch: 0. Loss: 2.3077569007873535. Accuracy: 10
Epoch: 1. Loss: 2.3313422203063965. Accuracy: 10
Epoch: 2. Loss: 2.3011667728424072. Accuracy: 10
Epoch: 3. Loss: 2.307199239730835. Accuracy: 10
Epoch: 4. Loss: 2.31876540184021. Accuracy: 10
Epoch: 5. Loss: 2.2914822101593018. Accuracy: 10
Epoch: 6. Loss: 2.297595977783203. Accuracy: 10
Epoch: 7. Loss: 2.313068389892578. Accuracy: 10
Epoch: 8. Loss: 2.3014626502990723. Accuracy: 10
Epoch: 9. Loss: 2.303609848022461. Accuracy: 10
Epoch: 10. Loss: 2.3071186542510986. Accuracy: 10
Epoch: 11. Loss: 2.30769681930542. Accuracy: 10
Epoch: 12. Loss: 2.297297716140747. Accuracy: 10
Epoch: 13. Loss: 2.3041789531707764. Accuracy: 10
Epoch: 14. Loss: 2.30816388130188. Accuracy: 10
[ 0.060040727520174746 256 tensor(10) ]
Loss: 2.30816388130188
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0971179659875861

Epoch: 0. Loss: 2.285391092300415. Accuracy: 10
Epoch: 1. Loss: 2.3367514610290527. Accuracy: 10
Epoch: 2. Loss: 2.307213306427002. Accuracy: 10
Epoch: 3. Loss: 2.298060655593872. Accuracy: 10
Epoch: 4. Loss: 2.310924768447876. Accuracy: 10
Epoch: 5. Loss: 2.2906196117401123. Accuracy: 10
Epoch: 6. Loss: 2.326540231704712. Accuracy: 10
Epoch: 7. Loss: 2.272932767868042. Accuracy: 10
Epoch: 8. Loss: 2.334893226623535. Accuracy: 10
Epoch: 9. Loss: 2.38714861869812. Accuracy: 10
Epoch: 10. Loss: 2.3249852657318115. Accuracy: 10
Epoch: 11. Loss: 2.3388936519622803. Accuracy: 10
Epoch: 12. Loss: 2.2841219902038574. Accuracy: 10
Epoch: 13. Loss: 2.2904982566833496. Accuracy: 10
Epoch: 14. Loss: 2.265644073486328. Accuracy: 10
[ 0.0971179659875861 32 tensor(10) ]
Loss: 2.265644073486328
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.08398009583309954

Epoch: 0. Loss: 2.3197529315948486. Accuracy: 10
Epoch: 1. Loss: 2.309924602508545. Accuracy: 10
Epoch: 2. Loss: 2.3183882236480713. Accuracy: 10
Epoch: 3. Loss: 2.308555841445923. Accuracy: 10
Epoch: 4. Loss: 2.2894504070281982. Accuracy: 10
Epoch: 5. Loss: 2.299211263656616. Accuracy: 10
Epoch: 6. Loss: 2.3109991550445557. Accuracy: 10
Epoch: 7. Loss: 2.307711362838745. Accuracy: 10
Epoch: 8. Loss: 2.3084285259246826. Accuracy: 10
Epoch: 9. Loss: 2.303621530532837. Accuracy: 10
Epoch: 10. Loss: 2.3104450702667236. Accuracy: 10
Epoch: 11. Loss: 2.3028695583343506. Accuracy: 10
Epoch: 12. Loss: 2.309159517288208. Accuracy: 10
Epoch: 13. Loss: 2.3104453086853027. Accuracy: 10
Epoch: 14. Loss: 2.303454875946045. Accuracy: 10
[ 0.08398009583309954 128 tensor(10) ]
Loss: 2.303454875946045
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.04271400014145438

Epoch: 0. Loss: 0.6960191130638123. Accuracy: 64
Epoch: 1. Loss: 0.5488080978393555. Accuracy: 65
Epoch: 2. Loss: 0.5514114499092102. Accuracy: 64
Epoch: 3. Loss: 0.6432718634605408. Accuracy: 66
Epoch: 4. Loss: 0.8735461235046387. Accuracy: 62
Epoch: 5. Loss: 0.4583515226840973. Accuracy: 66
Epoch: 6. Loss: 0.5536921620368958. Accuracy: 65
Epoch: 7. Loss: 0.6597165465354919. Accuracy: 65
Epoch: 8. Loss: 0.6378815770149231. Accuracy: 65
Epoch: 9. Loss: 0.3734947144985199. Accuracy: 66
Epoch: 10. Loss: 0.5486288070678711. Accuracy: 66
Epoch: 11. Loss: 0.821378767490387. Accuracy: 66
Epoch: 12. Loss: 0.5079202055931091. Accuracy: 68
Epoch: 13. Loss: 0.5278889536857605. Accuracy: 68
Epoch: 14. Loss: 0.6025542616844177. Accuracy: 65
[ 0.04271400014145438 128 tensor(65) ]
Loss: 0.6025542616844177
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.09272856767489271

Epoch: 0. Loss: 2.3082168102264404. Accuracy: 10
Epoch: 1. Loss: 2.306562662124634. Accuracy: 10
Epoch: 2. Loss: 2.306084632873535. Accuracy: 10
Epoch: 3. Loss: 2.305572271347046. Accuracy: 10
Epoch: 4. Loss: 2.3092024326324463. Accuracy: 10
Epoch: 5. Loss: 2.3261780738830566. Accuracy: 10
Epoch: 6. Loss: 2.3095390796661377. Accuracy: 10
Epoch: 7. Loss: 2.2966296672821045. Accuracy: 10
Epoch: 8. Loss: 2.3051013946533203. Accuracy: 10
Epoch: 9. Loss: 2.3023173809051514. Accuracy: 10
Epoch: 10. Loss: 2.2993199825286865. Accuracy: 10
Epoch: 11. Loss: 2.299898624420166. Accuracy: 10
Epoch: 12. Loss: 2.303675889968872. Accuracy: 10
Epoch: 13. Loss: 2.310933828353882. Accuracy: 10
Epoch: 14. Loss: 2.308246374130249. Accuracy: 10
[ 0.09272856767489271 256 tensor(10) ]
Loss: 2.308246374130249
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.01183144235869823

Epoch: 0. Loss: 0.631161093711853. Accuracy: 85
Epoch: 1. Loss: 0.3883425295352936. Accuracy: 85
Epoch: 2. Loss: 0.3178446292877197. Accuracy: 86
Epoch: 3. Loss: 0.1782691925764084. Accuracy: 87
Epoch: 4. Loss: 0.1356738954782486. Accuracy: 87
Epoch: 5. Loss: 0.17315994203090668. Accuracy: 86
Epoch: 6. Loss: 0.07629172503948212. Accuracy: 88
Epoch: 7. Loss: 0.026460930705070496. Accuracy: 88
Epoch: 8. Loss: 0.35527503490448. Accuracy: 88
Epoch: 9. Loss: 0.007457360625267029. Accuracy: 88
Epoch: 10. Loss: 0.07785609364509583. Accuracy: 88
Epoch: 11. Loss: 0.22464331984519958. Accuracy: 88
Epoch: 12. Loss: 0.06958482414484024. Accuracy: 87
Epoch: 13. Loss: 0.12777721881866455. Accuracy: 87
Epoch: 14. Loss: 0.01626339554786682. Accuracy: 88
[ 0.01183144235869823 64 tensor(88) ]
Loss: 0.01626339554786682
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.02250339274874771

Epoch: 0. Loss: 0.43709152936935425. Accuracy: 66
Epoch: 1. Loss: 0.9863719940185547. Accuracy: 67
Epoch: 2. Loss: 0.921631395816803. Accuracy: 66
Epoch: 3. Loss: 0.3965742588043213. Accuracy: 64
Epoch: 4. Loss: 0.304024338722229. Accuracy: 71
Epoch: 5. Loss: 0.2167285829782486. Accuracy: 75
Epoch: 6. Loss: 0.3830256462097168. Accuracy: 73
Epoch: 7. Loss: 0.24954093992710114. Accuracy: 76
Epoch: 8. Loss: 0.25109243392944336. Accuracy: 78
Epoch: 9. Loss: 0.3680577278137207. Accuracy: 75
Epoch: 10. Loss: 0.4423159956932068. Accuracy: 77
Epoch: 11. Loss: 0.6232344508171082. Accuracy: 75
Epoch: 12. Loss: 0.302774041891098. Accuracy: 76
Epoch: 13. Loss: 0.1637728065252304. Accuracy: 79
Epoch: 14. Loss: 0.23357263207435608. Accuracy: 79
[ 0.02250339274874771 32 tensor(79) ]
Loss: 0.23357263207435608
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.08429888676690869

Epoch: 0. Loss: 2.311431646347046. Accuracy: 10
Epoch: 1. Loss: 2.298811912536621. Accuracy: 10
Epoch: 2. Loss: 2.294318914413452. Accuracy: 10
Epoch: 3. Loss: 2.307572364807129. Accuracy: 10
Epoch: 4. Loss: 2.3073136806488037. Accuracy: 10
Epoch: 5. Loss: 2.3175408840179443. Accuracy: 10
Epoch: 6. Loss: 2.3058316707611084. Accuracy: 10
Epoch: 7. Loss: 2.3096227645874023. Accuracy: 10
Epoch: 8. Loss: 2.3034298419952393. Accuracy: 10
Epoch: 9. Loss: 2.311983108520508. Accuracy: 10
Epoch: 10. Loss: 2.306673526763916. Accuracy: 10
Epoch: 11. Loss: 2.297109365463257. Accuracy: 10
Epoch: 12. Loss: 2.3066976070404053. Accuracy: 10
Epoch: 13. Loss: 2.293048143386841. Accuracy: 10
Epoch: 14. Loss: 2.3056037425994873. Accuracy: 10
[ 0.08429888676690869 256 tensor(10) ]
Loss: 2.3056037425994873
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.007108099497397989

Epoch: 0. Loss: 0.11718547344207764. Accuracy: 87
Epoch: 1. Loss: 0.30289310216903687. Accuracy: 88
Epoch: 2. Loss: 0.04450477659702301. Accuracy: 89
Epoch: 3. Loss: 0.16460254788398743. Accuracy: 89
Epoch: 4. Loss: 0.14171046018600464. Accuracy: 89
Epoch: 5. Loss: 0.08589605987071991. Accuracy: 89
Epoch: 6. Loss: 0.12627841532230377. Accuracy: 88
Epoch: 7. Loss: 0.13971924781799316. Accuracy: 89
Epoch: 8. Loss: 0.04188866913318634. Accuracy: 90
Epoch: 9. Loss: 0.1643451601266861. Accuracy: 90
Epoch: 10. Loss: 0.15307003259658813. Accuracy: 89
Epoch: 11. Loss: 0.04645518958568573. Accuracy: 89
Epoch: 12. Loss: 0.014180049300193787. Accuracy: 89
Epoch: 13. Loss: 0.014451034367084503. Accuracy: 89
Epoch: 14. Loss: 0.0359070748090744. Accuracy: 90
[ 0.007108099497397989 32 tensor(90) ]
Loss: 0.0359070748090744
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.09704368761372752

Epoch: 0. Loss: 2.2950048446655273. Accuracy: 10
Epoch: 1. Loss: 2.3041882514953613. Accuracy: 10
Epoch: 2. Loss: 2.330353021621704. Accuracy: 10
Epoch: 3. Loss: 2.3398618698120117. Accuracy: 10
Epoch: 4. Loss: 2.2831523418426514. Accuracy: 10
Epoch: 5. Loss: 2.2985498905181885. Accuracy: 10
Epoch: 6. Loss: 2.311030387878418. Accuracy: 10
Epoch: 7. Loss: 2.29118013381958. Accuracy: 10
Epoch: 8. Loss: 2.2790796756744385. Accuracy: 10
Epoch: 9. Loss: 2.3351333141326904. Accuracy: 10
Epoch: 10. Loss: 2.2862789630889893. Accuracy: 10
Epoch: 11. Loss: 2.3376412391662598. Accuracy: 10
Epoch: 12. Loss: 2.3419556617736816. Accuracy: 10
Epoch: 13. Loss: 2.301598072052002. Accuracy: 10
Epoch: 14. Loss: 2.4169790744781494. Accuracy: 10
[ 0.09704368761372752 32 tensor(10) ]
Loss: 2.4169790744781494
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.07726386898176812

Epoch: 0. Loss: 2.3498551845550537. Accuracy: 10
Epoch: 1. Loss: 2.282040596008301. Accuracy: 10
Epoch: 2. Loss: 2.3295719623565674. Accuracy: 10
Epoch: 3. Loss: 2.3420019149780273. Accuracy: 10
Epoch: 4. Loss: 2.3251543045043945. Accuracy: 10
Epoch: 5. Loss: 2.2871081829071045. Accuracy: 10
Epoch: 6. Loss: 2.322873115539551. Accuracy: 10
Epoch: 7. Loss: 2.2765657901763916. Accuracy: 10
Epoch: 8. Loss: 2.3129725456237793. Accuracy: 10
Epoch: 9. Loss: 2.2655832767486572. Accuracy: 10
Epoch: 10. Loss: 2.2889564037323. Accuracy: 10
Epoch: 11. Loss: 2.313833475112915. Accuracy: 10
Epoch: 12. Loss: 2.283745050430298. Accuracy: 10
Epoch: 13. Loss: 2.306922197341919. Accuracy: 10
Epoch: 14. Loss: 2.292583465576172. Accuracy: 10
[ 0.07726386898176812 64 tensor(10) ]
Loss: 2.292583465576172
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.0043654988308221765

Epoch: 0. Loss: 0.325311541557312. Accuracy: 87
Epoch: 1. Loss: 0.23693746328353882. Accuracy: 90
Epoch: 2. Loss: 0.04785136133432388. Accuracy: 91
Epoch: 3. Loss: 0.09606172144412994. Accuracy: 91
Epoch: 4. Loss: 0.028149142861366272. Accuracy: 92
Epoch: 5. Loss: 0.04847700148820877. Accuracy: 91
Epoch: 6. Loss: 0.09094451367855072. Accuracy: 91
Epoch: 7. Loss: 0.2051060050725937. Accuracy: 92
Epoch: 8. Loss: 0.012463122606277466. Accuracy: 92
Epoch: 9. Loss: 0.005236715078353882. Accuracy: 91
Epoch: 10. Loss: 0.010847806930541992. Accuracy: 92
Epoch: 11. Loss: 0.0043382346630096436. Accuracy: 92
Epoch: 12. Loss: 0.0027031749486923218. Accuracy: 91
Epoch: 13. Loss: 0.021471768617630005. Accuracy: 91
Epoch: 14. Loss: 0.021435625851154327. Accuracy: 92
[ 0.0043654988308221765 64 tensor(92) ]
Loss: 0.021435625851154327
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.01896780390597324

Epoch: 0. Loss: 0.44500648975372314. Accuracy: 78
Epoch: 1. Loss: 0.2801109850406647. Accuracy: 77
Epoch: 2. Loss: 0.18073612451553345. Accuracy: 79
Epoch: 3. Loss: 0.17424853146076202. Accuracy: 80
Epoch: 4. Loss: 0.258962482213974. Accuracy: 79
Epoch: 5. Loss: 0.2700929343700409. Accuracy: 80
Epoch: 6. Loss: 0.5110812187194824. Accuracy: 79
Epoch: 7. Loss: 0.21068350970745087. Accuracy: 79
Epoch: 8. Loss: 0.4720735549926758. Accuracy: 79
Epoch: 9. Loss: 0.32713958621025085. Accuracy: 80
Epoch: 10. Loss: 0.21948282420635223. Accuracy: 80
Epoch: 11. Loss: 0.29643794894218445. Accuracy: 80
Epoch: 12. Loss: 0.18749575316905975. Accuracy: 81
Epoch: 13. Loss: 0.39354196190834045. Accuracy: 82
Epoch: 14. Loss: 0.21283797919750214. Accuracy: 82
[ 0.01896780390597324 128 tensor(82) ]
Loss: 0.21283797919750214
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.0009337273156990241

Epoch: 0. Loss: 0.2579098641872406. Accuracy: 79
Epoch: 1. Loss: 0.2587909996509552. Accuracy: 83
Epoch: 2. Loss: 0.12190049886703491. Accuracy: 86
Epoch: 3. Loss: 0.20199519395828247. Accuracy: 86
Epoch: 4. Loss: 0.26402145624160767. Accuracy: 87
Epoch: 5. Loss: 0.12243326753377914. Accuracy: 89
Epoch: 6. Loss: 0.10174358636140823. Accuracy: 89
Epoch: 7. Loss: 0.216464564204216. Accuracy: 90
Epoch: 8. Loss: 0.1574496477842331. Accuracy: 90
Epoch: 9. Loss: 0.108029305934906. Accuracy: 90
Epoch: 10. Loss: 0.09450778365135193. Accuracy: 90
Epoch: 11. Loss: 0.05173458531498909. Accuracy: 90
Epoch: 12. Loss: 0.043797265738248825. Accuracy: 91
Epoch: 13. Loss: 0.08698045462369919. Accuracy: 91
Epoch: 14. Loss: 0.092168889939785. Accuracy: 91
[ 0.0009337273156990241 128 tensor(91) ]
Loss: 0.092168889939785
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.001267261962815322

Epoch: 0. Loss: 0.38944754004478455. Accuracy: 85
Epoch: 1. Loss: 0.14118961989879608. Accuracy: 87
Epoch: 2. Loss: 0.13047659397125244. Accuracy: 89
Epoch: 3. Loss: 0.23669545352458954. Accuracy: 90
Epoch: 4. Loss: 0.020953357219696045. Accuracy: 90
Epoch: 5. Loss: 0.03535360097885132. Accuracy: 91
Epoch: 6. Loss: 0.015752650797367096. Accuracy: 91
Epoch: 7. Loss: 0.15860672295093536. Accuracy: 91
Epoch: 8. Loss: 0.01971857249736786. Accuracy: 91
Epoch: 9. Loss: 0.19924573600292206. Accuracy: 91
Epoch: 10. Loss: 0.0654333308339119. Accuracy: 92
Epoch: 11. Loss: 0.008003182709217072. Accuracy: 91
Epoch: 12. Loss: 0.010554846376180649. Accuracy: 91
Epoch: 13. Loss: 0.02728521078824997. Accuracy: 91
Epoch: 14. Loss: 0.03819979727268219. Accuracy: 91
[ 0.001267261962815322 32 tensor(91) ]
Loss: 0.03819979727268219
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.0064434254058602985

Epoch: 0. Loss: 0.13768912851810455. Accuracy: 88
Epoch: 1. Loss: 0.44024306535720825. Accuracy: 90
Epoch: 2. Loss: 0.039545103907585144. Accuracy: 90
Epoch: 3. Loss: 0.04246038198471069. Accuracy: 91
Epoch: 4. Loss: 0.27640628814697266. Accuracy: 91
Epoch: 5. Loss: 0.08064626157283783. Accuracy: 91
Epoch: 6. Loss: 0.1106138825416565. Accuracy: 91
Epoch: 7. Loss: 0.02740176022052765. Accuracy: 91
Epoch: 8. Loss: 0.02631395310163498. Accuracy: 92
Epoch: 9. Loss: 0.04259027540683746. Accuracy: 91
Epoch: 10. Loss: 0.08497937023639679. Accuracy: 91
Epoch: 11. Loss: 0.013407588005065918. Accuracy: 91
Epoch: 12. Loss: 0.04811789095401764. Accuracy: 90
Epoch: 13. Loss: 0.10311757028102875. Accuracy: 91
Epoch: 14. Loss: 0.0011159181594848633. Accuracy: 92
[ 0.0064434254058602985 64 tensor(92) ]
Loss: 0.0011159181594848633
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.01761076261894127

Epoch: 0. Loss: 0.1771250218153. Accuracy: 83
Epoch: 1. Loss: 0.16478818655014038. Accuracy: 85
Epoch: 2. Loss: 0.08433175832033157. Accuracy: 88
Epoch: 3. Loss: 0.03243106231093407. Accuracy: 88
Epoch: 4. Loss: 0.13763545453548431. Accuracy: 89
Epoch: 5. Loss: 0.3446122705936432. Accuracy: 88
Epoch: 6. Loss: 0.08642510324716568. Accuracy: 89
Epoch: 7. Loss: 0.07814037799835205. Accuracy: 89
Epoch: 8. Loss: 0.055039625614881516. Accuracy: 89
Epoch: 9. Loss: 0.18808066844940186. Accuracy: 88
Epoch: 10. Loss: 0.1466337889432907. Accuracy: 89
Epoch: 11. Loss: 0.10091332346200943. Accuracy: 89
Epoch: 12. Loss: 0.22134865820407867. Accuracy: 88
Epoch: 13. Loss: 0.09718707203865051. Accuracy: 88
Epoch: 14. Loss: 0.11310871690511703. Accuracy: 89
[ 0.01761076261894127 256 tensor(89) ]
Loss: 0.11310871690511703
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0891287331684087

Epoch: 0. Loss: 2.314237356185913. Accuracy: 10
Epoch: 1. Loss: 2.3265013694763184. Accuracy: 10
Epoch: 2. Loss: 2.31315016746521. Accuracy: 10
Epoch: 3. Loss: 2.3108339309692383. Accuracy: 10
Epoch: 4. Loss: 2.3357129096984863. Accuracy: 10
Epoch: 5. Loss: 2.33833384513855. Accuracy: 10
Epoch: 6. Loss: 2.3613574504852295. Accuracy: 10
Epoch: 7. Loss: 2.311089515686035. Accuracy: 10
Epoch: 8. Loss: 2.3076491355895996. Accuracy: 10
Epoch: 9. Loss: 2.338099241256714. Accuracy: 10
Epoch: 10. Loss: 2.3323872089385986. Accuracy: 10
Epoch: 11. Loss: 2.3223936557769775. Accuracy: 10
Epoch: 12. Loss: 2.342108964920044. Accuracy: 10
Epoch: 13. Loss: 2.2706775665283203. Accuracy: 10
Epoch: 14. Loss: 2.3618690967559814. Accuracy: 10
[ 0.0891287331684087 32 tensor(10) ]
Loss: 2.3618690967559814
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.06932423192989814

Epoch: 0. Loss: 0.6898181438446045. Accuracy: 65
Epoch: 1. Loss: 0.5939218401908875. Accuracy: 63
Epoch: 2. Loss: 0.6823113560676575. Accuracy: 66
Epoch: 3. Loss: 0.5721471309661865. Accuracy: 63
Epoch: 4. Loss: 0.9472370743751526. Accuracy: 53
Epoch: 5. Loss: 0.8425659537315369. Accuracy: 57
Epoch: 6. Loss: 0.7911636829376221. Accuracy: 58
Epoch: 7. Loss: 0.9893736839294434. Accuracy: 57
Epoch: 8. Loss: 0.9201338887214661. Accuracy: 59
Epoch: 9. Loss: 0.992821455001831. Accuracy: 59
Epoch: 10. Loss: 1.0661998987197876. Accuracy: 56
Epoch: 11. Loss: 0.8351345062255859. Accuracy: 58
Epoch: 12. Loss: 0.8006790280342102. Accuracy: 58
Epoch: 13. Loss: 0.850351870059967. Accuracy: 58
Epoch: 14. Loss: 0.9327394962310791. Accuracy: 56
[ 0.06932423192989814 128 tensor(56) ]
Loss: 0.9327394962310791
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.0054323669666178675

Epoch: 0. Loss: 0.32304665446281433. Accuracy: 83
Epoch: 1. Loss: 0.17636506259441376. Accuracy: 87
Epoch: 2. Loss: 0.11726313829421997. Accuracy: 89
Epoch: 3. Loss: 0.10735094547271729. Accuracy: 90
Epoch: 4. Loss: 0.11318019032478333. Accuracy: 90
Epoch: 5. Loss: 0.09775402396917343. Accuracy: 91
Epoch: 6. Loss: 0.06655915081501007. Accuracy: 91
Epoch: 7. Loss: 0.0914146900177002. Accuracy: 91
Epoch: 8. Loss: 0.08990409970283508. Accuracy: 92
Epoch: 9. Loss: 0.03858215734362602. Accuracy: 91
Epoch: 10. Loss: 0.07033247500658035. Accuracy: 92
Epoch: 11. Loss: 0.050149813294410706. Accuracy: 92
Epoch: 12. Loss: 0.07088875025510788. Accuracy: 91
Epoch: 13. Loss: 0.04849805310368538. Accuracy: 91
Epoch: 14. Loss: 0.11359746009111404. Accuracy: 91
[ 0.0054323669666178675 256 tensor(91) ]
Loss: 0.11359746009111404
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.046638518102352644

Epoch: 0. Loss: 0.31124377250671387. Accuracy: 77
Epoch: 1. Loss: 0.34459665417671204. Accuracy: 80
Epoch: 2. Loss: 0.453992635011673. Accuracy: 79
Epoch: 3. Loss: 0.48629915714263916. Accuracy: 79
Epoch: 4. Loss: 0.3338252007961273. Accuracy: 81
Epoch: 5. Loss: 0.38727259635925293. Accuracy: 80
Epoch: 6. Loss: 0.4440300166606903. Accuracy: 80
Epoch: 7. Loss: 0.29289934039115906. Accuracy: 81
Epoch: 8. Loss: 0.3107686936855316. Accuracy: 81
Epoch: 9. Loss: 0.33431681990623474. Accuracy: 78
Epoch: 10. Loss: 0.3240932524204254. Accuracy: 79
Epoch: 11. Loss: 0.270918607711792. Accuracy: 80
Epoch: 12. Loss: 0.303352028131485. Accuracy: 82
Epoch: 13. Loss: 0.22555822134017944. Accuracy: 79
Epoch: 14. Loss: 0.3246108591556549. Accuracy: 81
[ 0.046638518102352644 256 tensor(81) ]
Loss: 0.3246108591556549
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.006886690905460307

Epoch: 0. Loss: 0.12064620107412338. Accuracy: 85
Epoch: 1. Loss: 0.155986487865448. Accuracy: 86
Epoch: 2. Loss: 0.10041258484125137. Accuracy: 86
Epoch: 3. Loss: 0.38811272382736206. Accuracy: 87
Epoch: 4. Loss: 0.013251259922981262. Accuracy: 87
Epoch: 5. Loss: 0.0899420827627182. Accuracy: 88
Epoch: 6. Loss: 0.17240019142627716. Accuracy: 88
Epoch: 7. Loss: 0.1547398567199707. Accuracy: 88
Epoch: 8. Loss: 0.2820146381855011. Accuracy: 88
Epoch: 9. Loss: 0.20703794062137604. Accuracy: 87
Epoch: 10. Loss: 0.14464351534843445. Accuracy: 87
Epoch: 11. Loss: 0.029753178358078003. Accuracy: 88
Epoch: 12. Loss: 0.08053568005561829. Accuracy: 88
Epoch: 13. Loss: 0.08202515542507172. Accuracy: 87
Epoch: 14. Loss: 0.1177171915769577. Accuracy: 88
[ 0.006886690905460307 32 tensor(88) ]
Loss: 0.1177171915769577
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.0016429461446766784

Epoch: 0. Loss: 0.09901301562786102. Accuracy: 83
Epoch: 1. Loss: 0.10062504559755325. Accuracy: 88
Epoch: 2. Loss: 0.012627288699150085. Accuracy: 89
Epoch: 3. Loss: 0.03152453899383545. Accuracy: 90
Epoch: 4. Loss: 0.052015021443367004. Accuracy: 90
Epoch: 5. Loss: 0.08269340544939041. Accuracy: 90
Epoch: 6. Loss: 0.07174636423587799. Accuracy: 91
Epoch: 7. Loss: 0.17081916332244873. Accuracy: 91
Epoch: 8. Loss: 0.18326623737812042. Accuracy: 91
Epoch: 9. Loss: 0.008021607995033264. Accuracy: 92
Epoch: 10. Loss: 0.020470604300498962. Accuracy: 91
Epoch: 11. Loss: 0.05381755530834198. Accuracy: 91
Epoch: 12. Loss: 0.02893345057964325. Accuracy: 92
Epoch: 13. Loss: 0.06940669566392899. Accuracy: 92
Epoch: 14. Loss: 0.10667410492897034. Accuracy: 91
[ 0.0016429461446766784 64 tensor(91) ]
Loss: 0.10667410492897034
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.09326947906845177

Epoch: 0. Loss: 0.9280019402503967. Accuracy: 56
Epoch: 1. Loss: 0.6296490430831909. Accuracy: 57
Epoch: 2. Loss: 0.7633035182952881. Accuracy: 58
Epoch: 3. Loss: 0.7633419036865234. Accuracy: 47
Epoch: 4. Loss: 0.7940280437469482. Accuracy: 57
Epoch: 5. Loss: 0.8350418210029602. Accuracy: 58
Epoch: 6. Loss: 0.9506911635398865. Accuracy: 58
Epoch: 7. Loss: 0.9181280136108398. Accuracy: 56
Epoch: 8. Loss: 0.8263747692108154. Accuracy: 58
Epoch: 9. Loss: 0.9169972538948059. Accuracy: 57
Epoch: 10. Loss: 1.233069658279419. Accuracy: 57
Epoch: 11. Loss: 0.8318274617195129. Accuracy: 58
Epoch: 12. Loss: 1.0151046514511108. Accuracy: 58
Epoch: 13. Loss: 0.8186383843421936. Accuracy: 58
Epoch: 14. Loss: 0.6175809502601624. Accuracy: 58
[ 0.09326947906845177 256 tensor(58) ]
Loss: 0.6175809502601624
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0319833971154068

Epoch: 0. Loss: 0.7853010892868042. Accuracy: 57
Epoch: 1. Loss: 0.5633436441421509. Accuracy: 57
Epoch: 2. Loss: 0.8147817254066467. Accuracy: 55
Epoch: 3. Loss: 0.9043547511100769. Accuracy: 55
Epoch: 4. Loss: 1.1092787981033325. Accuracy: 57
Epoch: 5. Loss: 0.5814051628112793. Accuracy: 56
Epoch: 6. Loss: 0.990411102771759. Accuracy: 56
Epoch: 7. Loss: 0.8352248668670654. Accuracy: 58
Epoch: 8. Loss: 0.9209024906158447. Accuracy: 58
Epoch: 9. Loss: 0.7318889498710632. Accuracy: 56
Epoch: 10. Loss: 0.566332221031189. Accuracy: 57
Epoch: 11. Loss: 1.4157522916793823. Accuracy: 57
Epoch: 12. Loss: 0.7182817459106445. Accuracy: 58
Epoch: 13. Loss: 0.7280099391937256. Accuracy: 58
Epoch: 14. Loss: 0.9010829925537109. Accuracy: 53
[ 0.0319833971154068 32 tensor(53) ]
Loss: 0.9010829925537109
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.06229217407957104

Epoch: 0. Loss: 0.45019903779029846. Accuracy: 70
Epoch: 1. Loss: 0.5402663946151733. Accuracy: 72
Epoch: 2. Loss: 0.41781696677207947. Accuracy: 69
Epoch: 3. Loss: 0.4712434709072113. Accuracy: 71
Epoch: 4. Loss: 0.3770565688610077. Accuracy: 70
Epoch: 5. Loss: 0.3880733549594879. Accuracy: 71
Epoch: 6. Loss: 0.5955314636230469. Accuracy: 70
Epoch: 7. Loss: 0.6304415464401245. Accuracy: 72
Epoch: 8. Loss: 0.42594799399375916. Accuracy: 71
Epoch: 9. Loss: 0.4285860061645508. Accuracy: 70
Epoch: 10. Loss: 0.5525549650192261. Accuracy: 71
Epoch: 11. Loss: 0.5340563654899597. Accuracy: 72
Epoch: 12. Loss: 0.44341909885406494. Accuracy: 72
Epoch: 13. Loss: 0.6387346982955933. Accuracy: 71
Epoch: 14. Loss: 0.539882481098175. Accuracy: 71
[ 0.06229217407957104 256 tensor(71) ]
Loss: 0.539882481098175
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.05150891791154296

Epoch: 0. Loss: 2.31030535697937. Accuracy: 10
Epoch: 1. Loss: 2.310659885406494. Accuracy: 10
Epoch: 2. Loss: 2.308866500854492. Accuracy: 10
Epoch: 3. Loss: 2.311067581176758. Accuracy: 10
Epoch: 4. Loss: 2.310142993927002. Accuracy: 10
Epoch: 5. Loss: 2.30186128616333. Accuracy: 10
Epoch: 6. Loss: 2.301931619644165. Accuracy: 10
Epoch: 7. Loss: 2.3067069053649902. Accuracy: 10
Epoch: 8. Loss: 2.2964985370635986. Accuracy: 10
Epoch: 9. Loss: 2.3115859031677246. Accuracy: 10
Epoch: 10. Loss: 2.298281669616699. Accuracy: 10
Epoch: 11. Loss: 2.3215219974517822. Accuracy: 10
Epoch: 12. Loss: 2.3285446166992188. Accuracy: 10
Epoch: 13. Loss: 2.337181329727173. Accuracy: 10
Epoch: 14. Loss: 2.3071670532226562. Accuracy: 10
[ 0.05150891791154296 32 tensor(10) ]
Loss: 2.3071670532226562
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.0006167009259250069

Epoch: 0. Loss: 0.25835996866226196. Accuracy: 79
Epoch: 1. Loss: 0.17461802065372467. Accuracy: 84
Epoch: 2. Loss: 0.18703149259090424. Accuracy: 86
Epoch: 3. Loss: 0.05057826638221741. Accuracy: 86
Epoch: 4. Loss: 0.07176268845796585. Accuracy: 88
Epoch: 5. Loss: 0.07717429101467133. Accuracy: 88
Epoch: 6. Loss: 0.008545160293579102. Accuracy: 89
Epoch: 7. Loss: 0.07119058072566986. Accuracy: 90
Epoch: 8. Loss: 0.13625448942184448. Accuracy: 89
Epoch: 9. Loss: 0.10023218393325806. Accuracy: 90
Epoch: 10. Loss: 0.008988946676254272. Accuracy: 90
Epoch: 11. Loss: 0.08000488579273224. Accuracy: 90
Epoch: 12. Loss: 0.04701690748333931. Accuracy: 91
Epoch: 13. Loss: 0.012353084981441498. Accuracy: 90
Epoch: 14. Loss: 0.11409322172403336. Accuracy: 90
[ 0.0006167009259250069 64 tensor(90) ]
Loss: 0.11409322172403336
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.05020652989328417

Epoch: 0. Loss: 2.334959030151367. Accuracy: 10
Epoch: 1. Loss: 2.3441600799560547. Accuracy: 10
Epoch: 2. Loss: 2.306638479232788. Accuracy: 10
Epoch: 3. Loss: 2.3022985458374023. Accuracy: 10
Epoch: 4. Loss: 2.317564010620117. Accuracy: 10
Epoch: 5. Loss: 2.3009965419769287. Accuracy: 10
Epoch: 6. Loss: 2.3117642402648926. Accuracy: 10
Epoch: 7. Loss: 2.317167043685913. Accuracy: 10
Epoch: 8. Loss: 2.2976741790771484. Accuracy: 10
Epoch: 9. Loss: 2.3218207359313965. Accuracy: 10
Epoch: 10. Loss: 2.293253183364868. Accuracy: 10
Epoch: 11. Loss: 2.3162548542022705. Accuracy: 10
Epoch: 12. Loss: 2.2987091541290283. Accuracy: 10
Epoch: 13. Loss: 2.2963833808898926. Accuracy: 10
Epoch: 14. Loss: 2.293745279312134. Accuracy: 10
[ 0.05020652989328417 64 tensor(10) ]
Loss: 2.293745279312134
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.05003848513546204

Epoch: 0. Loss: 2.3373470306396484. Accuracy: 10
Epoch: 1. Loss: 2.295870304107666. Accuracy: 10
Epoch: 2. Loss: 2.3432226181030273. Accuracy: 10
Epoch: 3. Loss: 2.30558705329895. Accuracy: 10
Epoch: 4. Loss: 2.298308849334717. Accuracy: 10
Epoch: 5. Loss: 2.3213181495666504. Accuracy: 10
Epoch: 6. Loss: 2.297194004058838. Accuracy: 10
Epoch: 7. Loss: 2.2959694862365723. Accuracy: 10
Epoch: 8. Loss: 2.341641902923584. Accuracy: 10
Epoch: 9. Loss: 2.298112630844116. Accuracy: 10
Epoch: 10. Loss: 2.3367671966552734. Accuracy: 10
Epoch: 11. Loss: 2.2948732376098633. Accuracy: 10
Epoch: 12. Loss: 2.3136086463928223. Accuracy: 10
Epoch: 13. Loss: 2.2933685779571533. Accuracy: 10
Epoch: 14. Loss: 2.3282973766326904. Accuracy: 10
[ 0.05003848513546204 64 tensor(10) ]
Loss: 2.3282973766326904
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.03683820545839452

Epoch: 0. Loss: 0.8992051482200623. Accuracy: 57
Epoch: 1. Loss: 1.0203768014907837. Accuracy: 62
Epoch: 2. Loss: 0.969729483127594. Accuracy: 60
Epoch: 3. Loss: 0.7499963641166687. Accuracy: 62
Epoch: 4. Loss: 0.9030153155326843. Accuracy: 61
Epoch: 5. Loss: 0.7600631713867188. Accuracy: 62
Epoch: 6. Loss: 0.6759252548217773. Accuracy: 60
Epoch: 7. Loss: 0.8037848472595215. Accuracy: 63
Epoch: 8. Loss: 0.6525328755378723. Accuracy: 62
Epoch: 9. Loss: 0.727515459060669. Accuracy: 61
Epoch: 10. Loss: 0.5410107970237732. Accuracy: 65
Epoch: 11. Loss: 0.48641231656074524. Accuracy: 69
Epoch: 12. Loss: 0.532823383808136. Accuracy: 69
Epoch: 13. Loss: 0.5704525709152222. Accuracy: 70
Epoch: 14. Loss: 0.6634883880615234. Accuracy: 71
[ 0.03683820545839452 256 tensor(71) ]
Loss: 0.6634883880615234
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0152562249640162

Epoch: 0. Loss: 2.300631523132324. Accuracy: 10
Epoch: 1. Loss: 2.3061349391937256. Accuracy: 10
Epoch: 2. Loss: 2.301485776901245. Accuracy: 10
Epoch: 3. Loss: 2.313359498977661. Accuracy: 10
Epoch: 4. Loss: 2.31302809715271. Accuracy: 10
Epoch: 5. Loss: 2.2871952056884766. Accuracy: 10
Epoch: 6. Loss: 2.300525188446045. Accuracy: 10
Epoch: 7. Loss: 2.3174877166748047. Accuracy: 10
Epoch: 8. Loss: 2.2968881130218506. Accuracy: 10
Epoch: 9. Loss: 2.2942023277282715. Accuracy: 10
Epoch: 10. Loss: 2.30057430267334. Accuracy: 10
Epoch: 11. Loss: 2.349121332168579. Accuracy: 10
Epoch: 12. Loss: 2.29471755027771. Accuracy: 10
Epoch: 13. Loss: 2.2976174354553223. Accuracy: 10
Epoch: 14. Loss: 2.299650192260742. Accuracy: 10
[ 0.0152562249640162 32 tensor(10) ]
Loss: 2.299650192260742
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.040186149688562225

Epoch: 0. Loss: 0.8016074299812317. Accuracy: 65
Epoch: 1. Loss: 0.9348552823066711. Accuracy: 67
Epoch: 2. Loss: 0.5238463282585144. Accuracy: 65
Epoch: 3. Loss: 0.5678666830062866. Accuracy: 66
Epoch: 4. Loss: 0.9667677283287048. Accuracy: 66
Epoch: 5. Loss: 0.6028274893760681. Accuracy: 66
Epoch: 6. Loss: 0.9863131046295166. Accuracy: 66
Epoch: 7. Loss: 0.6683639883995056. Accuracy: 65
Epoch: 8. Loss: 0.9260209202766418. Accuracy: 67
Epoch: 9. Loss: 0.5293545126914978. Accuracy: 66
Epoch: 10. Loss: 0.28351837396621704. Accuracy: 67
Epoch: 11. Loss: 1.249374270439148. Accuracy: 63
Epoch: 12. Loss: 0.2579770088195801. Accuracy: 67
Epoch: 13. Loss: 0.7240704298019409. Accuracy: 66
Epoch: 14. Loss: 0.3806403875350952. Accuracy: 64
[ 0.040186149688562225 64 tensor(64) ]
Loss: 0.3806403875350952
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0408429677283232

Epoch: 0. Loss: 2.304851770401001. Accuracy: 10
Epoch: 1. Loss: 2.2747745513916016. Accuracy: 10
Epoch: 2. Loss: 2.2806236743927. Accuracy: 10
Epoch: 3. Loss: 2.3154666423797607. Accuracy: 10
Epoch: 4. Loss: 2.2981021404266357. Accuracy: 10
Epoch: 5. Loss: 2.3359217643737793. Accuracy: 10
Epoch: 6. Loss: 2.291471004486084. Accuracy: 10
Epoch: 7. Loss: 2.3184707164764404. Accuracy: 10
Epoch: 8. Loss: 2.3298864364624023. Accuracy: 10
Epoch: 9. Loss: 2.325362205505371. Accuracy: 10
Epoch: 10. Loss: 2.289628028869629. Accuracy: 10
Epoch: 11. Loss: 2.315486431121826. Accuracy: 10
Epoch: 12. Loss: 2.3149607181549072. Accuracy: 10
Epoch: 13. Loss: 2.28586483001709. Accuracy: 10
Epoch: 14. Loss: 2.2934648990631104. Accuracy: 10
[ 0.0408429677283232 32 tensor(10) ]
Loss: 2.2934648990631104
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.06635600476352224

Epoch: 0. Loss: 2.309081792831421. Accuracy: 10
Epoch: 1. Loss: 2.3054425716400146. Accuracy: 10
Epoch: 2. Loss: 2.30104660987854. Accuracy: 10
Epoch: 3. Loss: 2.308397054672241. Accuracy: 10
Epoch: 4. Loss: 2.2991116046905518. Accuracy: 10
Epoch: 5. Loss: 2.298903226852417. Accuracy: 10
Epoch: 6. Loss: 2.301903009414673. Accuracy: 10
Epoch: 7. Loss: 2.3161728382110596. Accuracy: 10
Epoch: 8. Loss: 2.303253412246704. Accuracy: 10
Epoch: 9. Loss: 2.308406114578247. Accuracy: 10
Epoch: 10. Loss: 2.3013017177581787. Accuracy: 10
Epoch: 11. Loss: 2.287435531616211. Accuracy: 10
Epoch: 12. Loss: 2.2940077781677246. Accuracy: 10
Epoch: 13. Loss: 2.2958972454071045. Accuracy: 10
Epoch: 14. Loss: 2.3122684955596924. Accuracy: 10
[ 0.06635600476352224 128 tensor(10) ]
Loss: 2.3122684955596924
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.09861027466673157

Epoch: 0. Loss: 2.322608709335327. Accuracy: 10
Epoch: 1. Loss: 2.304835081100464. Accuracy: 10
Epoch: 2. Loss: 2.3248109817504883. Accuracy: 10
Epoch: 3. Loss: 2.313664674758911. Accuracy: 10
Epoch: 4. Loss: 2.3088223934173584. Accuracy: 10
Epoch: 5. Loss: 2.297168731689453. Accuracy: 10
Epoch: 6. Loss: 2.294874668121338. Accuracy: 10
Epoch: 7. Loss: 2.315706491470337. Accuracy: 10
Epoch: 8. Loss: 2.313084363937378. Accuracy: 10
Epoch: 9. Loss: 2.3182690143585205. Accuracy: 10
Epoch: 10. Loss: 2.3174376487731934. Accuracy: 10
Epoch: 11. Loss: 2.3133394718170166. Accuracy: 10
Epoch: 12. Loss: 2.3070261478424072. Accuracy: 10
Epoch: 13. Loss: 2.3196990489959717. Accuracy: 10
Epoch: 14. Loss: 2.3015387058258057. Accuracy: 10
[ 0.09861027466673157 64 tensor(10) ]
Loss: 2.3015387058258057
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.03763082518227249

Epoch: 0. Loss: 0.8646126389503479. Accuracy: 54
Epoch: 1. Loss: 0.9312822818756104. Accuracy: 55
Epoch: 2. Loss: 0.745944082736969. Accuracy: 56
Epoch: 3. Loss: 1.0368815660476685. Accuracy: 56
Epoch: 4. Loss: 0.8367404937744141. Accuracy: 55
Epoch: 5. Loss: 1.1051801443099976. Accuracy: 55
Epoch: 6. Loss: 0.8752356171607971. Accuracy: 53
Epoch: 7. Loss: 1.0212279558181763. Accuracy: 54
Epoch: 8. Loss: 1.0772227048873901. Accuracy: 54
Epoch: 9. Loss: 0.8322155475616455. Accuracy: 54
Epoch: 10. Loss: 0.8088135123252869. Accuracy: 56
Epoch: 11. Loss: 0.8229618072509766. Accuracy: 57
Epoch: 12. Loss: 0.8580871224403381. Accuracy: 55
Epoch: 13. Loss: 1.0609909296035767. Accuracy: 55
Epoch: 14. Loss: 0.9218563437461853. Accuracy: 55
[ 0.03763082518227249 128 tensor(55) ]
Loss: 0.9218563437461853
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.009183309650950919

Epoch: 0. Loss: 0.18354155123233795. Accuracy: 85
Epoch: 1. Loss: 0.151615172624588. Accuracy: 87
Epoch: 2. Loss: 0.056679606437683105. Accuracy: 87
Epoch: 3. Loss: 0.12702378630638123. Accuracy: 87
Epoch: 4. Loss: 0.12168900668621063. Accuracy: 88
Epoch: 5. Loss: 0.11666104197502136. Accuracy: 88
Epoch: 6. Loss: 0.03390650451183319. Accuracy: 88
Epoch: 7. Loss: 0.06902507692575455. Accuracy: 89
Epoch: 8. Loss: 0.06055368483066559. Accuracy: 88
Epoch: 9. Loss: 0.04715330898761749. Accuracy: 87
Epoch: 10. Loss: 0.042866677045822144. Accuracy: 89
Epoch: 11. Loss: 0.1916915774345398. Accuracy: 89
Epoch: 12. Loss: 0.012893930077552795. Accuracy: 88
Epoch: 13. Loss: 0.1471022218465805. Accuracy: 88
Epoch: 14. Loss: 0.014474645256996155. Accuracy: 87
[ 0.009183309650950919 64 tensor(87) ]
Loss: 0.014474645256996155
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.07073930087811373

Epoch: 0. Loss: 2.3085947036743164. Accuracy: 10
Epoch: 1. Loss: 2.3218181133270264. Accuracy: 10
Epoch: 2. Loss: 2.3091819286346436. Accuracy: 10
Epoch: 3. Loss: 2.314206838607788. Accuracy: 10
Epoch: 4. Loss: 2.328061103820801. Accuracy: 10
Epoch: 5. Loss: 2.2867846488952637. Accuracy: 10
Epoch: 6. Loss: 2.3547980785369873. Accuracy: 10
Epoch: 7. Loss: 2.3290886878967285. Accuracy: 10
Epoch: 8. Loss: 2.3154845237731934. Accuracy: 10
Epoch: 9. Loss: 2.345207691192627. Accuracy: 10
Epoch: 10. Loss: 2.291995048522949. Accuracy: 10
Epoch: 11. Loss: 2.324437379837036. Accuracy: 10
Epoch: 12. Loss: 2.272547960281372. Accuracy: 10
Epoch: 13. Loss: 2.2995383739471436. Accuracy: 10
Epoch: 14. Loss: 2.3116562366485596. Accuracy: 10
[ 0.07073930087811373 32 tensor(10) ]
Loss: 2.3116562366485596
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.04050246827273392

Epoch: 0. Loss: 0.8828722238540649. Accuracy: 53
Epoch: 1. Loss: 0.6759345531463623. Accuracy: 53
Epoch: 2. Loss: 0.9263260364532471. Accuracy: 53
Epoch: 3. Loss: 0.8188677430152893. Accuracy: 54
Epoch: 4. Loss: 0.6224344968795776. Accuracy: 55
Epoch: 5. Loss: 0.9465154409408569. Accuracy: 52
Epoch: 6. Loss: 0.9590836763381958. Accuracy: 56
Epoch: 7. Loss: 0.7979682683944702. Accuracy: 56
Epoch: 8. Loss: 0.9881598353385925. Accuracy: 30
Epoch: 9. Loss: 1.06071138381958. Accuracy: 55
Epoch: 10. Loss: 0.9814618229866028. Accuracy: 54
Epoch: 11. Loss: 0.760226309299469. Accuracy: 55
Epoch: 12. Loss: 0.8095319867134094. Accuracy: 54
Epoch: 13. Loss: 0.9654995799064636. Accuracy: 56
Epoch: 14. Loss: 0.7049887180328369. Accuracy: 55
[ 0.04050246827273392 64 tensor(55) ]
Loss: 0.7049887180328369
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0294214936903096

Epoch: 0. Loss: 2.294480562210083. Accuracy: 10
Epoch: 1. Loss: 2.3072335720062256. Accuracy: 10
Epoch: 2. Loss: 2.2898383140563965. Accuracy: 10
Epoch: 3. Loss: 2.270076036453247. Accuracy: 10
Epoch: 4. Loss: 2.3050665855407715. Accuracy: 10
Epoch: 5. Loss: 2.320563316345215. Accuracy: 10
Epoch: 6. Loss: 2.3184635639190674. Accuracy: 10
Epoch: 7. Loss: 2.295883893966675. Accuracy: 10
Epoch: 8. Loss: 2.299299478530884. Accuracy: 10
Epoch: 9. Loss: 2.3055546283721924. Accuracy: 10
Epoch: 10. Loss: 2.3029985427856445. Accuracy: 10
Epoch: 11. Loss: 2.303936004638672. Accuracy: 10
Epoch: 12. Loss: 2.283717632293701. Accuracy: 10
Epoch: 13. Loss: 2.311643362045288. Accuracy: 10
Epoch: 14. Loss: 2.3067431449890137. Accuracy: 10
[ 0.0294214936903096 32 tensor(10) ]
Loss: 2.3067431449890137
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.015118369813407551

Epoch: 0. Loss: 0.22210511565208435. Accuracy: 81
Epoch: 1. Loss: 0.12631507217884064. Accuracy: 78
Epoch: 2. Loss: 0.21352535486221313. Accuracy: 82
Epoch: 3. Loss: 0.23806200921535492. Accuracy: 80
Epoch: 4. Loss: 0.07469873130321503. Accuracy: 82
Epoch: 5. Loss: 0.4707295298576355. Accuracy: 83
Epoch: 6. Loss: 0.1129469946026802. Accuracy: 84
Epoch: 7. Loss: 0.2775220572948456. Accuracy: 84
Epoch: 8. Loss: 0.22494032979011536. Accuracy: 83
Epoch: 9. Loss: 0.18219627439975739. Accuracy: 84
Epoch: 10. Loss: 0.6695319414138794. Accuracy: 82
Epoch: 11. Loss: 0.08584311604499817. Accuracy: 83
Epoch: 12. Loss: 0.048038169741630554. Accuracy: 84
Epoch: 13. Loss: 0.3212975263595581. Accuracy: 84
Epoch: 14. Loss: 0.47601285576820374. Accuracy: 85
[ 0.015118369813407551 32 tensor(85) ]
Loss: 0.47601285576820374
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.018836371781095013

Epoch: 0. Loss: 0.7244593501091003. Accuracy: 59
Epoch: 1. Loss: 0.7576054930686951. Accuracy: 62
Epoch: 2. Loss: 1.0791093111038208. Accuracy: 61
Epoch: 3. Loss: 0.38662388920783997. Accuracy: 61
Epoch: 4. Loss: 0.6724134683609009. Accuracy: 63
Epoch: 5. Loss: 0.824826717376709. Accuracy: 61
Epoch: 6. Loss: 0.5342406630516052. Accuracy: 61
Epoch: 7. Loss: 0.6759887337684631. Accuracy: 62
Epoch: 8. Loss: 1.1089307069778442. Accuracy: 60
Epoch: 9. Loss: 0.8038537502288818. Accuracy: 60
Epoch: 10. Loss: 0.5222630500793457. Accuracy: 62
Epoch: 11. Loss: 0.7708972692489624. Accuracy: 62
Epoch: 12. Loss: 0.8212894201278687. Accuracy: 62
Epoch: 13. Loss: 0.9390313625335693. Accuracy: 61
Epoch: 14. Loss: 1.1096508502960205. Accuracy: 61
[ 0.018836371781095013 64 tensor(61) ]
Loss: 1.1096508502960205
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.05751513913583711

Epoch: 0. Loss: 2.3174257278442383. Accuracy: 10
Epoch: 1. Loss: 2.313138723373413. Accuracy: 10
Epoch: 2. Loss: 2.311469316482544. Accuracy: 10
Epoch: 3. Loss: 2.2794077396392822. Accuracy: 10
Epoch: 4. Loss: 2.3223536014556885. Accuracy: 10
Epoch: 5. Loss: 2.310250759124756. Accuracy: 10
Epoch: 6. Loss: 2.2971179485321045. Accuracy: 10
Epoch: 7. Loss: 2.3184874057769775. Accuracy: 10
Epoch: 8. Loss: 2.307662010192871. Accuracy: 10
Epoch: 9. Loss: 2.3232216835021973. Accuracy: 10
Epoch: 10. Loss: 2.3185439109802246. Accuracy: 10
Epoch: 11. Loss: 2.302865982055664. Accuracy: 10
Epoch: 12. Loss: 2.31528639793396. Accuracy: 10
Epoch: 13. Loss: 2.3303849697113037. Accuracy: 10
Epoch: 14. Loss: 2.333442449569702. Accuracy: 10
[ 0.05751513913583711 32 tensor(10) ]
Loss: 2.333442449569702
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.006533249372131163

Epoch: 0. Loss: 0.08575154095888138. Accuracy: 84
Epoch: 1. Loss: 0.1406484842300415. Accuracy: 84
Epoch: 2. Loss: 0.28479745984077454. Accuracy: 88
Epoch: 3. Loss: 0.0807030200958252. Accuracy: 88
Epoch: 4. Loss: 0.13443782925605774. Accuracy: 88
Epoch: 5. Loss: 0.1729772537946701. Accuracy: 88
Epoch: 6. Loss: 0.025164812803268433. Accuracy: 88
Epoch: 7. Loss: 0.14787445962429047. Accuracy: 89
Epoch: 8. Loss: 0.06953751295804977. Accuracy: 87
Epoch: 9. Loss: 0.11293412744998932. Accuracy: 89
Epoch: 10. Loss: 0.0243757963180542. Accuracy: 89
Epoch: 11. Loss: 0.13296499848365784. Accuracy: 87
Epoch: 12. Loss: 0.08328279107809067. Accuracy: 88
Epoch: 13. Loss: 0.17567801475524902. Accuracy: 88
Epoch: 14. Loss: 0.17107895016670227. Accuracy: 89
[ 0.006533249372131163 64 tensor(89) ]
Loss: 0.17107895016670227
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.006424479865882137

Epoch: 0. Loss: 0.22227615118026733. Accuracy: 86
Epoch: 1. Loss: 0.05418691784143448. Accuracy: 88
Epoch: 2. Loss: 0.017844751477241516. Accuracy: 89
Epoch: 3. Loss: 0.09981515258550644. Accuracy: 89
Epoch: 4. Loss: 0.014905467629432678. Accuracy: 89
Epoch: 5. Loss: 0.04096990078687668. Accuracy: 89
Epoch: 6. Loss: 0.011403247714042664. Accuracy: 90
Epoch: 7. Loss: 0.012870639562606812. Accuracy: 89
Epoch: 8. Loss: 0.03791327029466629. Accuracy: 90
Epoch: 9. Loss: 0.0804804340004921. Accuracy: 90
Epoch: 10. Loss: 0.11131516098976135. Accuracy: 89
Epoch: 11. Loss: 0.037278495728969574. Accuracy: 90
Epoch: 12. Loss: 0.1682550460100174. Accuracy: 89
Epoch: 13. Loss: 0.011812835931777954. Accuracy: 89
Epoch: 14. Loss: 0.021482259035110474. Accuracy: 89
[ 0.006424479865882137 64 tensor(89) ]
Loss: 0.021482259035110474
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0025514448673918224

Epoch: 0. Loss: 0.06379028409719467. Accuracy: 85
Epoch: 1. Loss: 0.2147851586341858. Accuracy: 87
Epoch: 2. Loss: 0.10126318037509918. Accuracy: 88
Epoch: 3. Loss: 0.016879618167877197. Accuracy: 89
Epoch: 4. Loss: 0.0728176012635231. Accuracy: 90
Epoch: 5. Loss: 0.10189641267061234. Accuracy: 90
Epoch: 6. Loss: 0.012979388236999512. Accuracy: 90
Epoch: 7. Loss: 0.028077885508537292. Accuracy: 91
Epoch: 8. Loss: 0.17433221638202667. Accuracy: 91
Epoch: 9. Loss: 0.08216971904039383. Accuracy: 91
Epoch: 10. Loss: 0.12042306363582611. Accuracy: 91
Epoch: 11. Loss: 0.08445493876934052. Accuracy: 91
Epoch: 12. Loss: 0.06804045289754868. Accuracy: 91
Epoch: 13. Loss: 0.015423133969306946. Accuracy: 91
Epoch: 14. Loss: 0.2444630265235901. Accuracy: 90
[ 0.0025514448673918224 32 tensor(90) ]
Loss: 0.2444630265235901
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0005147039690743564

Epoch: 0. Loss: 0.5743499994277954. Accuracy: 80
Epoch: 1. Loss: 0.17811278998851776. Accuracy: 85
Epoch: 2. Loss: 0.08147598803043365. Accuracy: 87
Epoch: 3. Loss: 0.14479047060012817. Accuracy: 89
Epoch: 4. Loss: 0.10454549640417099. Accuracy: 89
Epoch: 5. Loss: 0.03216389939188957. Accuracy: 90
Epoch: 6. Loss: 0.060157984495162964. Accuracy: 90
Epoch: 7. Loss: 0.01266450434923172. Accuracy: 90
Epoch: 8. Loss: 0.03500959277153015. Accuracy: 90
Epoch: 9. Loss: 0.030908115208148956. Accuracy: 91
Epoch: 10. Loss: 0.01721913367509842. Accuracy: 91
Epoch: 11. Loss: 0.008586414158344269. Accuracy: 90
Epoch: 12. Loss: 0.023733798414468765. Accuracy: 91
Epoch: 13. Loss: 0.01245935633778572. Accuracy: 91
Epoch: 14. Loss: 0.23641720414161682. Accuracy: 91
[ 0.0005147039690743564 32 tensor(91) ]
Loss: 0.23641720414161682
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.003798472099939485

Epoch: 0. Loss: 0.07165015488862991. Accuracy: 87
Epoch: 1. Loss: 0.08052919805049896. Accuracy: 89
Epoch: 2. Loss: 0.10603722929954529. Accuracy: 90
Epoch: 3. Loss: 0.08197057247161865. Accuracy: 91
Epoch: 4. Loss: 0.16652150452136993. Accuracy: 92
Epoch: 5. Loss: 0.02257055789232254. Accuracy: 91
Epoch: 6. Loss: 0.13585788011550903. Accuracy: 91
Epoch: 7. Loss: 0.12736794352531433. Accuracy: 92
Epoch: 8. Loss: 0.023219585418701172. Accuracy: 91
Epoch: 9. Loss: 0.010576017200946808. Accuracy: 91
Epoch: 10. Loss: 0.06621241569519043. Accuracy: 91
Epoch: 11. Loss: 0.005277842283248901. Accuracy: 92
Epoch: 12. Loss: 0.0746554359793663. Accuracy: 91
Epoch: 13. Loss: 0.0037173032760620117. Accuracy: 92
Epoch: 14. Loss: 0.0036445260047912598. Accuracy: 91
[ 0.003798472099939485 64 tensor(91) ]
Loss: 0.0036445260047912598
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.0036810778783810125

Epoch: 0. Loss: 0.2940990924835205. Accuracy: 88
Epoch: 1. Loss: 0.23422308266162872. Accuracy: 90
Epoch: 2. Loss: 0.34783026576042175. Accuracy: 91
Epoch: 3. Loss: 0.10167598724365234. Accuracy: 91
Epoch: 4. Loss: 0.021507441997528076. Accuracy: 92
Epoch: 5. Loss: 0.02313261479139328. Accuracy: 91
Epoch: 6. Loss: 0.12958326935768127. Accuracy: 91
Epoch: 7. Loss: 0.12359912693500519. Accuracy: 91
Epoch: 8. Loss: 0.02276640385389328. Accuracy: 92
Epoch: 9. Loss: 0.24996984004974365. Accuracy: 92
Epoch: 10. Loss: 0.008611075580120087. Accuracy: 91
Epoch: 11. Loss: 0.023376867175102234. Accuracy: 91
Epoch: 12. Loss: 0.005205631256103516. Accuracy: 92
Epoch: 13. Loss: 0.028755798935890198. Accuracy: 92
Epoch: 14. Loss: 0.0027185827493667603. Accuracy: 92
[ 0.0036810778783810125 64 tensor(92) ]
Loss: 0.0027185827493667603
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.022686918693466313

Epoch: 0. Loss: 0.6965965628623962. Accuracy: 68
Epoch: 1. Loss: 0.5049567222595215. Accuracy: 70
Epoch: 2. Loss: 0.4890843629837036. Accuracy: 71
Epoch: 3. Loss: 0.3698783218860626. Accuracy: 72
Epoch: 4. Loss: 0.6300046443939209. Accuracy: 71
Epoch: 5. Loss: 0.3663445711135864. Accuracy: 71
Epoch: 6. Loss: 0.4941939413547516. Accuracy: 71
Epoch: 7. Loss: 0.5717055201530457. Accuracy: 72
Epoch: 8. Loss: 0.5188177824020386. Accuracy: 71
Epoch: 9. Loss: 0.3668335974216461. Accuracy: 71
Epoch: 10. Loss: 0.3983131945133209. Accuracy: 70
Epoch: 11. Loss: 0.5519241690635681. Accuracy: 72
Epoch: 12. Loss: 0.4161503314971924. Accuracy: 71
Epoch: 13. Loss: 0.42844533920288086. Accuracy: 72
Epoch: 14. Loss: 0.7630455493927002. Accuracy: 72
[ 0.022686918693466313 128 tensor(72) ]
Loss: 0.7630455493927002
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.038038179207636566

Epoch: 0. Loss: 0.9994485974311829. Accuracy: 56
Epoch: 1. Loss: 0.8128349184989929. Accuracy: 56
Epoch: 2. Loss: 1.2173019647598267. Accuracy: 57
Epoch: 3. Loss: 0.9269444942474365. Accuracy: 56
Epoch: 4. Loss: 1.0066194534301758. Accuracy: 54
Epoch: 5. Loss: 0.8280429244041443. Accuracy: 58
Epoch: 6. Loss: 0.8700426816940308. Accuracy: 54
Epoch: 7. Loss: 0.8748384118080139. Accuracy: 56
Epoch: 8. Loss: 0.7362566590309143. Accuracy: 58
Epoch: 9. Loss: 0.7266676425933838. Accuracy: 58
Epoch: 10. Loss: 1.0197811126708984. Accuracy: 57
Epoch: 11. Loss: 0.6011009812355042. Accuracy: 56
Epoch: 12. Loss: 0.7883301973342896. Accuracy: 56
Epoch: 13. Loss: 0.7427657246589661. Accuracy: 58
Epoch: 14. Loss: 0.8635896444320679. Accuracy: 33
[ 0.038038179207636566 32 tensor(33) ]
Loss: 0.8635896444320679
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.0318987691773682

Epoch: 0. Loss: 0.3752199709415436. Accuracy: 75
Epoch: 1. Loss: 0.3685455620288849. Accuracy: 78
Epoch: 2. Loss: 0.4396081268787384. Accuracy: 80
Epoch: 3. Loss: 0.4369034469127655. Accuracy: 80
Epoch: 4. Loss: 0.427852064371109. Accuracy: 79
Epoch: 5. Loss: 0.3881628215312958. Accuracy: 81
Epoch: 6. Loss: 0.4241534471511841. Accuracy: 81
Epoch: 7. Loss: 0.3990122973918915. Accuracy: 81
Epoch: 8. Loss: 0.2626866400241852. Accuracy: 80
Epoch: 9. Loss: 0.2251293659210205. Accuracy: 81
Epoch: 10. Loss: 0.3371868133544922. Accuracy: 80
Epoch: 11. Loss: 0.20553375780582428. Accuracy: 78
Epoch: 12. Loss: 0.2703500986099243. Accuracy: 82
Epoch: 13. Loss: 0.24182158708572388. Accuracy: 80
Epoch: 14. Loss: 0.3831069767475128. Accuracy: 79
[ 0.0318987691773682 256 tensor(79) ]
Loss: 0.3831069767475128
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.05552005626127902

Epoch: 0. Loss: 0.5836702585220337. Accuracy: 60
Epoch: 1. Loss: 0.6953503489494324. Accuracy: 65
Epoch: 2. Loss: 1.0024909973144531. Accuracy: 67
Epoch: 3. Loss: 0.6652653217315674. Accuracy: 67
Epoch: 4. Loss: 0.6568643450737. Accuracy: 65
Epoch: 5. Loss: 0.7854810357093811. Accuracy: 66
Epoch: 6. Loss: 0.540774405002594. Accuracy: 66
Epoch: 7. Loss: 0.5886251926422119. Accuracy: 67
Epoch: 8. Loss: 0.5311146974563599. Accuracy: 65
Epoch: 9. Loss: 0.6012322306632996. Accuracy: 65
Epoch: 10. Loss: 0.6328414082527161. Accuracy: 67
Epoch: 11. Loss: 0.5615695118904114. Accuracy: 69
Epoch: 12. Loss: 0.5219705700874329. Accuracy: 64
Epoch: 13. Loss: 0.5028831362724304. Accuracy: 68
Epoch: 14. Loss: 0.7589049339294434. Accuracy: 66
[ 0.05552005626127902 256 tensor(66) ]
Loss: 0.7589049339294434
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.06090353068312485

Epoch: 0. Loss: 2.29945969581604. Accuracy: 10
Epoch: 1. Loss: 2.3098416328430176. Accuracy: 10
Epoch: 2. Loss: 2.302736282348633. Accuracy: 10
Epoch: 3. Loss: 2.3215572834014893. Accuracy: 10
Epoch: 4. Loss: 2.3135621547698975. Accuracy: 10
Epoch: 5. Loss: 2.3148508071899414. Accuracy: 10
Epoch: 6. Loss: 2.302189826965332. Accuracy: 10
Epoch: 7. Loss: 2.294039487838745. Accuracy: 10
Epoch: 8. Loss: 2.2959272861480713. Accuracy: 10
Epoch: 9. Loss: 2.301609516143799. Accuracy: 10
Epoch: 10. Loss: 2.312803268432617. Accuracy: 10
Epoch: 11. Loss: 2.3076817989349365. Accuracy: 10
Epoch: 12. Loss: 2.297367811203003. Accuracy: 10
Epoch: 13. Loss: 2.310438632965088. Accuracy: 10
Epoch: 14. Loss: 2.300520181655884. Accuracy: 10
[ 0.06090353068312485 128 tensor(10) ]
Loss: 2.300520181655884
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.040087146718214825

Epoch: 0. Loss: 0.8493211269378662. Accuracy: 63
Epoch: 1. Loss: 0.4852282404899597. Accuracy: 65
Epoch: 2. Loss: 0.527965247631073. Accuracy: 65
Epoch: 3. Loss: 0.33033791184425354. Accuracy: 64
Epoch: 4. Loss: 0.8586778044700623. Accuracy: 66
Epoch: 5. Loss: 0.8567706942558289. Accuracy: 66
Epoch: 6. Loss: 0.5203061103820801. Accuracy: 63
Epoch: 7. Loss: 0.347260057926178. Accuracy: 65
Epoch: 8. Loss: 0.667726457118988. Accuracy: 63
Epoch: 9. Loss: 0.5655746459960938. Accuracy: 63
Epoch: 10. Loss: 0.3313574194908142. Accuracy: 64
Epoch: 11. Loss: 0.3033955693244934. Accuracy: 64
Epoch: 12. Loss: 1.2073252201080322. Accuracy: 66
Epoch: 13. Loss: 0.9843906164169312. Accuracy: 64
Epoch: 14. Loss: 0.8118677139282227. Accuracy: 66
[ 0.040087146718214825 64 tensor(66) ]
Loss: 0.8118677139282227
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.00645571390187681

Epoch: 0. Loss: 0.2056945115327835. Accuracy: 86
Epoch: 1. Loss: 0.14682930707931519. Accuracy: 89
Epoch: 2. Loss: 0.11046615988016129. Accuracy: 84
Epoch: 3. Loss: 0.1308639496564865. Accuracy: 90
Epoch: 4. Loss: 0.11686843633651733. Accuracy: 90
Epoch: 5. Loss: 0.00956505537033081. Accuracy: 90
Epoch: 6. Loss: 0.31401920318603516. Accuracy: 91
Epoch: 7. Loss: 0.11125276982784271. Accuracy: 91
Epoch: 8. Loss: 0.0435810387134552. Accuracy: 90
Epoch: 9. Loss: 0.14702723920345306. Accuracy: 90
Epoch: 10. Loss: 0.005741670727729797. Accuracy: 91
Epoch: 11. Loss: 0.04194527864456177. Accuracy: 91
Epoch: 12. Loss: 0.0027023255825042725. Accuracy: 91
Epoch: 13. Loss: 0.009275205433368683. Accuracy: 91
Epoch: 14. Loss: 0.27531641721725464. Accuracy: 90
[ 0.00645571390187681 64 tensor(90) ]
Loss: 0.27531641721725464
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.041178854205073855

Epoch: 0. Loss: 2.296060800552368. Accuracy: 10
Epoch: 1. Loss: 2.2862064838409424. Accuracy: 10
Epoch: 2. Loss: 2.2843918800354004. Accuracy: 10
Epoch: 3. Loss: 2.3069546222686768. Accuracy: 10
Epoch: 4. Loss: 2.301041841506958. Accuracy: 10
Epoch: 5. Loss: 2.323256254196167. Accuracy: 10
Epoch: 6. Loss: 2.3034565448760986. Accuracy: 10
Epoch: 7. Loss: 2.31307053565979. Accuracy: 10
Epoch: 8. Loss: 2.317582130432129. Accuracy: 23
Epoch: 9. Loss: 2.319927215576172. Accuracy: 10
Epoch: 10. Loss: 2.2953219413757324. Accuracy: 10
Epoch: 11. Loss: 2.385425329208374. Accuracy: 10
Epoch: 12. Loss: 2.2963662147521973. Accuracy: 10
Epoch: 13. Loss: 2.300079822540283. Accuracy: 10
Epoch: 14. Loss: 2.3059751987457275. Accuracy: 10
[ 0.041178854205073855 32 tensor(10) ]
Loss: 2.3059751987457275
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.07691019891107263

Epoch: 0. Loss: 2.3263731002807617. Accuracy: 10
Epoch: 1. Loss: 2.308079957962036. Accuracy: 10
Epoch: 2. Loss: 2.287903308868408. Accuracy: 10
Epoch: 3. Loss: 2.279493808746338. Accuracy: 10
Epoch: 4. Loss: 2.3491415977478027. Accuracy: 10
Epoch: 5. Loss: 2.294558048248291. Accuracy: 10
Epoch: 6. Loss: 2.3029274940490723. Accuracy: 10
Epoch: 7. Loss: 2.3360931873321533. Accuracy: 10
Epoch: 8. Loss: 2.325286388397217. Accuracy: 10
Epoch: 9. Loss: 2.294524669647217. Accuracy: 10
Epoch: 10. Loss: 2.319972038269043. Accuracy: 10
Epoch: 11. Loss: 2.314368486404419. Accuracy: 10
Epoch: 12. Loss: 2.324230670928955. Accuracy: 10
Epoch: 13. Loss: 2.344977378845215. Accuracy: 10
Epoch: 14. Loss: 2.257641077041626. Accuracy: 10
[ 0.07691019891107263 64 tensor(10) ]
Loss: 2.257641077041626
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.007363477808039578

Epoch: 0. Loss: 0.06680529564619064. Accuracy: 86
Epoch: 1. Loss: 0.14106294512748718. Accuracy: 88
Epoch: 2. Loss: 0.01671333611011505. Accuracy: 88
Epoch: 3. Loss: 0.11768507212400436. Accuracy: 89
Epoch: 4. Loss: 0.14651183784008026. Accuracy: 87
Epoch: 5. Loss: 0.07763808220624924. Accuracy: 89
Epoch: 6. Loss: 0.07147945463657379. Accuracy: 89
Epoch: 7. Loss: 0.04555992782115936. Accuracy: 89
Epoch: 8. Loss: 0.20987577736377716. Accuracy: 89
Epoch: 9. Loss: 0.00778062641620636. Accuracy: 89
Epoch: 10. Loss: 0.007290065288543701. Accuracy: 90
Epoch: 11. Loss: 0.12530314922332764. Accuracy: 89
Epoch: 12. Loss: 0.026836112141609192. Accuracy: 89
Epoch: 13. Loss: 0.05386573076248169. Accuracy: 89
Epoch: 14. Loss: 0.006340160965919495. Accuracy: 90
[ 0.007363477808039578 32 tensor(90) ]
Loss: 0.006340160965919495
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.005123932660982761

Epoch: 0. Loss: 0.1776612550020218. Accuracy: 82
Epoch: 1. Loss: 0.13715924322605133. Accuracy: 86
Epoch: 2. Loss: 0.10294697433710098. Accuracy: 88
Epoch: 3. Loss: 0.13586407899856567. Accuracy: 90
Epoch: 4. Loss: 0.21401143074035645. Accuracy: 90
Epoch: 5. Loss: 0.02090924233198166. Accuracy: 91
Epoch: 6. Loss: 0.023789092898368835. Accuracy: 92
Epoch: 7. Loss: 0.23515605926513672. Accuracy: 91
Epoch: 8. Loss: 0.1030210554599762. Accuracy: 91
Epoch: 9. Loss: 0.29750609397888184. Accuracy: 91
Epoch: 10. Loss: 0.0740252286195755. Accuracy: 91
Epoch: 11. Loss: 0.12414563447237015. Accuracy: 91
Epoch: 12. Loss: 0.016823703423142433. Accuracy: 91
Epoch: 13. Loss: 0.025626957416534424. Accuracy: 91
Epoch: 14. Loss: 0.06720292568206787. Accuracy: 92
[ 0.005123932660982761 256 tensor(92) ]
Loss: 0.06720292568206787
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.004452868853479381

Epoch: 0. Loss: 0.17530453205108643. Accuracy: 82
Epoch: 1. Loss: 0.12841065227985382. Accuracy: 86
Epoch: 2. Loss: 0.09267424792051315. Accuracy: 88
Epoch: 3. Loss: 0.18042729794979095. Accuracy: 89
Epoch: 4. Loss: 0.12657122313976288. Accuracy: 90
Epoch: 5. Loss: 0.04203983023762703. Accuracy: 90
Epoch: 6. Loss: 0.14108698070049286. Accuracy: 91
Epoch: 7. Loss: 0.07250780612230301. Accuracy: 91
Epoch: 8. Loss: 0.11134198307991028. Accuracy: 91
Epoch: 9. Loss: 0.20141887664794922. Accuracy: 92
Epoch: 10. Loss: 0.11598414182662964. Accuracy: 92
Epoch: 11. Loss: 0.06830684095621109. Accuracy: 92
Epoch: 12. Loss: 0.0933302715420723. Accuracy: 92
Epoch: 13. Loss: 0.1594592034816742. Accuracy: 92
Epoch: 14. Loss: 0.09195942431688309. Accuracy: 92
[ 0.004452868853479381 256 tensor(92) ]
Loss: 0.09195942431688309
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.033179843598560105

Epoch: 0. Loss: 0.4925002157688141. Accuracy: 70
Epoch: 1. Loss: 0.5252896547317505. Accuracy: 69
Epoch: 2. Loss: 0.5675942897796631. Accuracy: 70
Epoch: 3. Loss: 0.505095362663269. Accuracy: 71
Epoch: 4. Loss: 0.6398993134498596. Accuracy: 70
Epoch: 5. Loss: 0.5303888916969299. Accuracy: 71
Epoch: 6. Loss: 0.4123063385486603. Accuracy: 72
Epoch: 7. Loss: 0.5444653034210205. Accuracy: 70
Epoch: 8. Loss: 0.32873842120170593. Accuracy: 72
Epoch: 9. Loss: 0.3997240960597992. Accuracy: 74
Epoch: 10. Loss: 0.43095099925994873. Accuracy: 73
Epoch: 11. Loss: 0.38815680146217346. Accuracy: 73
Epoch: 12. Loss: 0.5183404088020325. Accuracy: 75
Epoch: 13. Loss: 0.6910857558250427. Accuracy: 74
Epoch: 14. Loss: 0.3442905843257904. Accuracy: 74
[ 0.033179843598560105 128 tensor(74) ]
Loss: 0.3442905843257904
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0004010948768473484

Epoch: 0. Loss: 0.41806888580322266. Accuracy: 79
Epoch: 1. Loss: 0.41011008620262146. Accuracy: 83
Epoch: 2. Loss: 0.0823025032877922. Accuracy: 85
Epoch: 3. Loss: 0.2377799153327942. Accuracy: 87
Epoch: 4. Loss: 0.199964702129364. Accuracy: 87
Epoch: 5. Loss: 0.3852381706237793. Accuracy: 89
Epoch: 6. Loss: 0.23080779612064362. Accuracy: 89
Epoch: 7. Loss: 0.0653078630566597. Accuracy: 90
Epoch: 8. Loss: 0.05397035926580429. Accuracy: 89
Epoch: 9. Loss: 0.04638670012354851. Accuracy: 90
Epoch: 10. Loss: 0.14360283315181732. Accuracy: 90
Epoch: 11. Loss: 0.13487841188907623. Accuracy: 90
Epoch: 12. Loss: 0.02431340515613556. Accuracy: 91
Epoch: 13. Loss: 0.10036426782608032. Accuracy: 90
Epoch: 14. Loss: 0.040426187217235565. Accuracy: 91
[ 0.0004010948768473484 32 tensor(91) ]
Loss: 0.040426187217235565
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.007083298140701556

Epoch: 0. Loss: 0.13876578211784363. Accuracy: 86
Epoch: 1. Loss: 0.05451768636703491. Accuracy: 87
Epoch: 2. Loss: 0.04362780600786209. Accuracy: 87
Epoch: 3. Loss: 0.02533099800348282. Accuracy: 88
Epoch: 4. Loss: 0.10251767188310623. Accuracy: 87
Epoch: 5. Loss: 0.11511551588773727. Accuracy: 88
Epoch: 6. Loss: 0.06718157976865768. Accuracy: 87
Epoch: 7. Loss: 0.05949408933520317. Accuracy: 88
Epoch: 8. Loss: 0.050024621188640594. Accuracy: 88
Epoch: 9. Loss: 0.15081018209457397. Accuracy: 88
Epoch: 10. Loss: 0.19545342028141022. Accuracy: 86
Epoch: 11. Loss: 0.14742417633533478. Accuracy: 87
Epoch: 12. Loss: 0.04228648543357849. Accuracy: 88
Epoch: 13. Loss: 0.09232457727193832. Accuracy: 89
Epoch: 14. Loss: 0.15372474491596222. Accuracy: 89
[ 0.007083298140701556 32 tensor(89) ]
Loss: 0.15372474491596222
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.019233864157220164

Epoch: 0. Loss: 0.2756541073322296. Accuracy: 76
Epoch: 1. Loss: 0.31153300404548645. Accuracy: 78
Epoch: 2. Loss: 0.2644251585006714. Accuracy: 80
Epoch: 3. Loss: 0.12492804229259491. Accuracy: 78
Epoch: 4. Loss: 0.3779071271419525. Accuracy: 79
Epoch: 5. Loss: 0.2277560830116272. Accuracy: 79
Epoch: 6. Loss: 0.21079450845718384. Accuracy: 80
Epoch: 7. Loss: 0.21515217423439026. Accuracy: 77
Epoch: 8. Loss: 0.207220658659935. Accuracy: 79
Epoch: 9. Loss: 0.37202104926109314. Accuracy: 80
Epoch: 10. Loss: 0.5596137642860413. Accuracy: 79
Epoch: 11. Loss: 0.32963359355926514. Accuracy: 81
Epoch: 12. Loss: 0.5320041179656982. Accuracy: 79
Epoch: 13. Loss: 0.31875622272491455. Accuracy: 78
Epoch: 14. Loss: 0.6880292892456055. Accuracy: 78
[ 0.019233864157220164 64 tensor(78) ]
Loss: 0.6880292892456055
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.0935350867442517

Epoch: 0. Loss: 2.323923349380493. Accuracy: 10
Epoch: 1. Loss: 2.307896852493286. Accuracy: 10
Epoch: 2. Loss: 2.3062551021575928. Accuracy: 10
Epoch: 3. Loss: 2.2985732555389404. Accuracy: 10
Epoch: 4. Loss: 2.3003275394439697. Accuracy: 10
Epoch: 5. Loss: 2.298985004425049. Accuracy: 10
Epoch: 6. Loss: 2.303544521331787. Accuracy: 10
Epoch: 7. Loss: 2.30572772026062. Accuracy: 10
Epoch: 8. Loss: 2.3330538272857666. Accuracy: 10
Epoch: 9. Loss: 2.3010244369506836. Accuracy: 10
Epoch: 10. Loss: 2.304854154586792. Accuracy: 10
Epoch: 11. Loss: 2.3076140880584717. Accuracy: 10
Epoch: 12. Loss: 2.302647829055786. Accuracy: 10
Epoch: 13. Loss: 2.2934582233428955. Accuracy: 10
Epoch: 14. Loss: 2.3099653720855713. Accuracy: 10
[ 0.0935350867442517 256 tensor(10) ]
Loss: 2.3099653720855713
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.014747758761414865

Epoch: 0. Loss: 0.36791422963142395. Accuracy: 76
Epoch: 1. Loss: 0.7101327776908875. Accuracy: 78
Epoch: 2. Loss: 0.7318831086158752. Accuracy: 76
Epoch: 3. Loss: 0.6058674454689026. Accuracy: 78
Epoch: 4. Loss: 0.6079964637756348. Accuracy: 77
Epoch: 5. Loss: 0.4605085253715515. Accuracy: 78
Epoch: 6. Loss: 0.516899585723877. Accuracy: 78
Epoch: 7. Loss: 0.1703224927186966. Accuracy: 78
Epoch: 8. Loss: 0.3471223711967468. Accuracy: 81
Epoch: 9. Loss: 0.30074241757392883. Accuracy: 81
Epoch: 10. Loss: 0.049023114144802094. Accuracy: 81
Epoch: 11. Loss: 0.15201042592525482. Accuracy: 82
Epoch: 12. Loss: 0.20778006315231323. Accuracy: 82
Epoch: 13. Loss: 0.28609514236450195. Accuracy: 81
Epoch: 14. Loss: 0.4522913992404938. Accuracy: 81
[ 0.014747758761414865 32 tensor(81) ]
Loss: 0.4522913992404938
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.008553162768929874

Epoch: 0. Loss: 0.34247756004333496. Accuracy: 84
Epoch: 1. Loss: 0.1427929848432541. Accuracy: 88
Epoch: 2. Loss: 0.02853924036026001. Accuracy: 88
Epoch: 3. Loss: 0.0220986008644104. Accuracy: 88
Epoch: 4. Loss: 0.2086123377084732. Accuracy: 89
Epoch: 5. Loss: 0.12382648885250092. Accuracy: 88
Epoch: 6. Loss: 0.1166486144065857. Accuracy: 87
Epoch: 7. Loss: 0.04325112700462341. Accuracy: 89
Epoch: 8. Loss: 0.026892274618148804. Accuracy: 89
Epoch: 9. Loss: 0.1815260946750641. Accuracy: 89
Epoch: 10. Loss: 0.30823665857315063. Accuracy: 89
Epoch: 11. Loss: 0.19738873839378357. Accuracy: 89
Epoch: 12. Loss: 0.01281052827835083. Accuracy: 89
Epoch: 13. Loss: 0.13801996409893036. Accuracy: 90
Epoch: 14. Loss: 0.17139475047588348. Accuracy: 90
[ 0.008553162768929874 64 tensor(90) ]
Loss: 0.17139475047588348
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.008150101732917579

Epoch: 0. Loss: 0.03404794633388519. Accuracy: 88
Epoch: 1. Loss: 0.021311745047569275. Accuracy: 89
Epoch: 2. Loss: 0.17131009697914124. Accuracy: 90
Epoch: 3. Loss: 0.11840388923883438. Accuracy: 90
Epoch: 4. Loss: 0.1724926084280014. Accuracy: 90
Epoch: 5. Loss: 0.021423086524009705. Accuracy: 91
Epoch: 6. Loss: 0.020325198769569397. Accuracy: 90
Epoch: 7. Loss: 0.01168869435787201. Accuracy: 91
Epoch: 8. Loss: 0.12220150232315063. Accuracy: 90
Epoch: 9. Loss: 0.2206026017665863. Accuracy: 91
Epoch: 10. Loss: 0.029913246631622314. Accuracy: 91
Epoch: 11. Loss: 0.12579743564128876. Accuracy: 91
Epoch: 12. Loss: 0.2997509241104126. Accuracy: 91
Epoch: 13. Loss: 0.43215933442115784. Accuracy: 91
Epoch: 14. Loss: 0.07328242063522339. Accuracy: 91
[ 0.008150101732917579 64 tensor(91) ]
Loss: 0.07328242063522339
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.005791875093868898

Epoch: 0. Loss: 0.31389766931533813. Accuracy: 82
Epoch: 1. Loss: 0.12598399817943573. Accuracy: 87
Epoch: 2. Loss: 0.12207209318876266. Accuracy: 89
Epoch: 3. Loss: 0.10290039330720901. Accuracy: 89
Epoch: 4. Loss: 0.06389690935611725. Accuracy: 89
Epoch: 5. Loss: 0.13597406446933746. Accuracy: 91
Epoch: 6. Loss: 0.06168743595480919. Accuracy: 90
Epoch: 7. Loss: 0.06306230276823044. Accuracy: 90
Epoch: 8. Loss: 0.1209588274359703. Accuracy: 90
Epoch: 9. Loss: 0.09611711651086807. Accuracy: 91
Epoch: 10. Loss: 0.017015933990478516. Accuracy: 91
Epoch: 11. Loss: 0.12238777428865433. Accuracy: 91
Epoch: 12. Loss: 0.08887740224599838. Accuracy: 91
Epoch: 13. Loss: 0.057611867785453796. Accuracy: 90
Epoch: 14. Loss: 0.053361330181360245. Accuracy: 91
[ 0.005791875093868898 256 tensor(91) ]
Loss: 0.053361330181360245
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.08364368804936473

Epoch: 0. Loss: 2.3041789531707764. Accuracy: 10
Epoch: 1. Loss: 2.3208467960357666. Accuracy: 10
Epoch: 2. Loss: 2.3113019466400146. Accuracy: 10
Epoch: 3. Loss: 2.3075692653656006. Accuracy: 10
Epoch: 4. Loss: 2.3087165355682373. Accuracy: 10
Epoch: 5. Loss: 2.319500207901001. Accuracy: 10
Epoch: 6. Loss: 2.3122665882110596. Accuracy: 10
Epoch: 7. Loss: 2.306213140487671. Accuracy: 10
Epoch: 8. Loss: 2.3078954219818115. Accuracy: 10
Epoch: 9. Loss: 2.301020383834839. Accuracy: 10
Epoch: 10. Loss: 2.286043882369995. Accuracy: 10
Epoch: 11. Loss: 2.2914063930511475. Accuracy: 10
Epoch: 12. Loss: 2.317425012588501. Accuracy: 10
Epoch: 13. Loss: 2.296684503555298. Accuracy: 10
Epoch: 14. Loss: 2.301149606704712. Accuracy: 10
[ 0.08364368804936473 128 tensor(10) ]
Loss: 2.301149606704712
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.029318120833776273

Epoch: 0. Loss: 0.8138956427574158. Accuracy: 67
Epoch: 1. Loss: 0.48917627334594727. Accuracy: 70
Epoch: 2. Loss: 0.4764650762081146. Accuracy: 67
Epoch: 3. Loss: 0.44628408551216125. Accuracy: 70
Epoch: 4. Loss: 0.7243456244468689. Accuracy: 69
Epoch: 5. Loss: 0.5739624500274658. Accuracy: 70
Epoch: 6. Loss: 0.5313807129859924. Accuracy: 71
Epoch: 7. Loss: 0.5950072407722473. Accuracy: 70
Epoch: 8. Loss: 0.5009756684303284. Accuracy: 73
Epoch: 9. Loss: 0.6148831248283386. Accuracy: 70
Epoch: 10. Loss: 0.8448324799537659. Accuracy: 70
Epoch: 11. Loss: 0.5896168351173401. Accuracy: 72
Epoch: 12. Loss: 0.5823435187339783. Accuracy: 70
Epoch: 13. Loss: 0.5359012484550476. Accuracy: 70
Epoch: 14. Loss: 0.5908578634262085. Accuracy: 71
[ 0.029318120833776273 128 tensor(71) ]
Loss: 0.5908578634262085
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.027033053463231246

Epoch: 0. Loss: 0.41559138894081116. Accuracy: 71
Epoch: 1. Loss: 0.42922699451446533. Accuracy: 73
Epoch: 2. Loss: 0.40586233139038086. Accuracy: 70
Epoch: 3. Loss: 0.332990437746048. Accuracy: 73
Epoch: 4. Loss: 0.3635481297969818. Accuracy: 72
Epoch: 5. Loss: 0.5065265893936157. Accuracy: 73
Epoch: 6. Loss: 0.47821441292762756. Accuracy: 71
Epoch: 7. Loss: 0.407247930765152. Accuracy: 74
Epoch: 8. Loss: 0.37239912152290344. Accuracy: 72
Epoch: 9. Loss: 0.48598572611808777. Accuracy: 73
Epoch: 10. Loss: 0.3405967652797699. Accuracy: 72
Epoch: 11. Loss: 0.6999791264533997. Accuracy: 67
Epoch: 12. Loss: 0.41783222556114197. Accuracy: 72
Epoch: 13. Loss: 0.36974847316741943. Accuracy: 74
Epoch: 14. Loss: 0.5216213464736938. Accuracy: 73
[ 0.027033053463231246 128 tensor(73) ]
Loss: 0.5216213464736938
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.010514793841057945

Epoch: 0. Loss: 0.2044452428817749. Accuracy: 85
Epoch: 1. Loss: 0.09138510376214981. Accuracy: 88
Epoch: 2. Loss: 0.2661650478839874. Accuracy: 88
Epoch: 3. Loss: 0.18443958461284637. Accuracy: 89
Epoch: 4. Loss: 0.11515546590089798. Accuracy: 89
Epoch: 5. Loss: 0.041200004518032074. Accuracy: 89
Epoch: 6. Loss: 0.030568720772862434. Accuracy: 89
Epoch: 7. Loss: 0.14784400165081024. Accuracy: 90
Epoch: 8. Loss: 0.07287681102752686. Accuracy: 89
Epoch: 9. Loss: 0.12952180206775665. Accuracy: 90
Epoch: 10. Loss: 0.08870556205511093. Accuracy: 90
Epoch: 11. Loss: 0.0533565990626812. Accuracy: 90
Epoch: 12. Loss: 0.05481569096446037. Accuracy: 91
Epoch: 13. Loss: 0.12422939389944077. Accuracy: 89
Epoch: 14. Loss: 0.10251177102327347. Accuracy: 90
[ 0.010514793841057945 128 tensor(90) ]
Loss: 0.10251177102327347
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.00898220226241335

Epoch: 0. Loss: 0.20835305750370026. Accuracy: 88
Epoch: 1. Loss: 0.15838949382305145. Accuracy: 90
Epoch: 2. Loss: 0.18551795184612274. Accuracy: 90
Epoch: 3. Loss: 0.08079933375120163. Accuracy: 91
Epoch: 4. Loss: 0.12577161192893982. Accuracy: 91
Epoch: 5. Loss: 0.08823224902153015. Accuracy: 91
Epoch: 6. Loss: 0.02026449143886566. Accuracy: 90
Epoch: 7. Loss: 0.17321963608264923. Accuracy: 92
Epoch: 8. Loss: 0.04582754895091057. Accuracy: 92
Epoch: 9. Loss: 0.13424257934093475. Accuracy: 92
Epoch: 10. Loss: 0.012827138416469097. Accuracy: 91
Epoch: 11. Loss: 0.1005864217877388. Accuracy: 92
Epoch: 12. Loss: 0.012669811956584454. Accuracy: 92
Epoch: 13. Loss: 0.06614459306001663. Accuracy: 92
Epoch: 14. Loss: 0.03260662779211998. Accuracy: 91
[ 0.00898220226241335 128 tensor(91) ]
Loss: 0.03260662779211998
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.02029306260987803

Epoch: 0. Loss: 0.41501349210739136. Accuracy: 76
Epoch: 1. Loss: 0.4868474304676056. Accuracy: 77
Epoch: 2. Loss: 0.5267821550369263. Accuracy: 73
Epoch: 3. Loss: 0.49742475152015686. Accuracy: 75
Epoch: 4. Loss: 0.2125505805015564. Accuracy: 75
Epoch: 5. Loss: 0.5070177912712097. Accuracy: 76
Epoch: 6. Loss: 0.23983709514141083. Accuracy: 76
Epoch: 7. Loss: 0.48083290457725525. Accuracy: 78
Epoch: 8. Loss: 0.22394336760044098. Accuracy: 77
Epoch: 9. Loss: 0.401015043258667. Accuracy: 76
Epoch: 10. Loss: 0.4234920144081116. Accuracy: 78
Epoch: 11. Loss: 0.45236197113990784. Accuracy: 77
Epoch: 12. Loss: 0.27304354310035706. Accuracy: 78
Epoch: 13. Loss: 0.6728425025939941. Accuracy: 77
Epoch: 14. Loss: 0.35079991817474365. Accuracy: 75
[ 0.02029306260987803 32 tensor(75) ]
Loss: 0.35079991817474365
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.09289844216938815

Epoch: 0. Loss: 1.1204173564910889. Accuracy: 51
Epoch: 1. Loss: 1.1125229597091675. Accuracy: 54
Epoch: 2. Loss: 2.3347690105438232. Accuracy: 10
Epoch: 3. Loss: 2.319666862487793. Accuracy: 10
Epoch: 4. Loss: 2.352128505706787. Accuracy: 10
Epoch: 5. Loss: 2.302156448364258. Accuracy: 10
Epoch: 6. Loss: 2.3197944164276123. Accuracy: 10
Epoch: 7. Loss: 2.3158986568450928. Accuracy: 10
Epoch: 8. Loss: 2.2955331802368164. Accuracy: 10
Epoch: 9. Loss: 2.3285062313079834. Accuracy: 10
Epoch: 10. Loss: 2.3293979167938232. Accuracy: 10
Epoch: 11. Loss: 2.287867307662964. Accuracy: 10
Epoch: 12. Loss: 2.315737247467041. Accuracy: 10
Epoch: 13. Loss: 2.293865203857422. Accuracy: 10
Epoch: 14. Loss: 2.3269870281219482. Accuracy: 10
[ 0.09289844216938815 32 tensor(10) ]
Loss: 2.3269870281219482
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.04938347318715898

Epoch: 0. Loss: 0.776190996170044. Accuracy: 59
Epoch: 1. Loss: 0.739673376083374. Accuracy: 59
Epoch: 2. Loss: 0.8874605298042297. Accuracy: 60
Epoch: 3. Loss: 0.6297021508216858. Accuracy: 65
Epoch: 4. Loss: 0.5244078040122986. Accuracy: 69
Epoch: 5. Loss: 0.5655799508094788. Accuracy: 73
Epoch: 6. Loss: 0.3486675024032593. Accuracy: 70
Epoch: 7. Loss: 0.41045740246772766. Accuracy: 71
Epoch: 8. Loss: 0.49538564682006836. Accuracy: 71
Epoch: 9. Loss: 0.43010544776916504. Accuracy: 71
Epoch: 10. Loss: 0.5816994309425354. Accuracy: 71
Epoch: 11. Loss: 0.5363744497299194. Accuracy: 70
Epoch: 12. Loss: 0.3808104991912842. Accuracy: 69
Epoch: 13. Loss: 0.6712589263916016. Accuracy: 71
Epoch: 14. Loss: 0.6602938771247864. Accuracy: 72
[ 0.04938347318715898 128 tensor(72) ]
Loss: 0.6602938771247864
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.07234762697847143

Epoch: 0. Loss: 2.3197646141052246. Accuracy: 10
Epoch: 1. Loss: 2.313861131668091. Accuracy: 10
Epoch: 2. Loss: 2.3146982192993164. Accuracy: 10
Epoch: 3. Loss: 2.3141062259674072. Accuracy: 10
Epoch: 4. Loss: 2.415201425552368. Accuracy: 10
Epoch: 5. Loss: 2.350085735321045. Accuracy: 10
Epoch: 6. Loss: 2.347653865814209. Accuracy: 10
Epoch: 7. Loss: 2.282536506652832. Accuracy: 10
Epoch: 8. Loss: 2.3189711570739746. Accuracy: 10
Epoch: 9. Loss: 2.311795234680176. Accuracy: 10
Epoch: 10. Loss: 2.3426153659820557. Accuracy: 10
Epoch: 11. Loss: 2.3373091220855713. Accuracy: 10
Epoch: 12. Loss: 2.274352550506592. Accuracy: 10
Epoch: 13. Loss: 2.2901227474212646. Accuracy: 10
Epoch: 14. Loss: 2.322242498397827. Accuracy: 10
[ 0.07234762697847143 64 tensor(10) ]
Loss: 2.322242498397827
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.004287834860539221

Epoch: 0. Loss: 0.10188174247741699. Accuracy: 86
Epoch: 1. Loss: 0.10430509597063065. Accuracy: 88
Epoch: 2. Loss: 0.13347378373146057. Accuracy: 89
Epoch: 3. Loss: 0.489980548620224. Accuracy: 87
Epoch: 4. Loss: 0.0672895684838295. Accuracy: 89
Epoch: 5. Loss: 0.10722538828849792. Accuracy: 89
Epoch: 6. Loss: 0.06297250092029572. Accuracy: 90
Epoch: 7. Loss: 0.016223236918449402. Accuracy: 88
Epoch: 8. Loss: 0.0816173180937767. Accuracy: 89
Epoch: 9. Loss: 0.09111924469470978. Accuracy: 91
Epoch: 10. Loss: 0.043789781630039215. Accuracy: 91
Epoch: 11. Loss: 0.05031178891658783. Accuracy: 90
Epoch: 12. Loss: 0.011859118938446045. Accuracy: 90
Epoch: 13. Loss: 0.08518488705158234. Accuracy: 90
Epoch: 14. Loss: 0.04998641461133957. Accuracy: 91
[ 0.004287834860539221 32 tensor(91) ]
Loss: 0.04998641461133957
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0058322247355213925

Epoch: 0. Loss: 0.5865112543106079. Accuracy: 86
Epoch: 1. Loss: 0.27923715114593506. Accuracy: 88
Epoch: 2. Loss: 0.03224214166402817. Accuracy: 89
Epoch: 3. Loss: 0.13186003267765045. Accuracy: 89
Epoch: 4. Loss: 0.04661576449871063. Accuracy: 90
Epoch: 5. Loss: 0.2203768789768219. Accuracy: 89
Epoch: 6. Loss: 0.025031715631484985. Accuracy: 89
Epoch: 7. Loss: 0.10766971856355667. Accuracy: 89
Epoch: 8. Loss: 0.035901039838790894. Accuracy: 90
Epoch: 9. Loss: 0.1976279318332672. Accuracy: 90
Epoch: 10. Loss: 0.039692044258117676. Accuracy: 90
Epoch: 11. Loss: 0.038216665387153625. Accuracy: 90
Epoch: 12. Loss: 0.08452807366847992. Accuracy: 90
Epoch: 13. Loss: 0.3438991606235504. Accuracy: 90
Epoch: 14. Loss: 0.0630309134721756. Accuracy: 90
[ 0.0058322247355213925 32 tensor(90) ]
Loss: 0.0630309134721756
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.0031053422448681523

Epoch: 0. Loss: 0.20473875105381012. Accuracy: 82
Epoch: 1. Loss: 0.18506436049938202. Accuracy: 87
Epoch: 2. Loss: 0.18200957775115967. Accuracy: 88
Epoch: 3. Loss: 0.05198421701788902. Accuracy: 89
Epoch: 4. Loss: 0.09464404731988907. Accuracy: 90
Epoch: 5. Loss: 0.060492295771837234. Accuracy: 90
Epoch: 6. Loss: 0.039060309529304504. Accuracy: 91
Epoch: 7. Loss: 0.054572876542806625. Accuracy: 91
Epoch: 8. Loss: 0.08522555232048035. Accuracy: 91
Epoch: 9. Loss: 0.08873654156923294. Accuracy: 91
Epoch: 10. Loss: 0.04355392977595329. Accuracy: 92
Epoch: 11. Loss: 0.016804667189717293. Accuracy: 91
Epoch: 12. Loss: 0.033634670078754425. Accuracy: 91
Epoch: 13. Loss: 0.12973058223724365. Accuracy: 92
Epoch: 14. Loss: 0.044435326009988785. Accuracy: 91
[ 0.0031053422448681523 128 tensor(91) ]
Loss: 0.044435326009988785
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.09107688132237185

Epoch: 0. Loss: 2.321734666824341. Accuracy: 10
Epoch: 1. Loss: 2.3051280975341797. Accuracy: 10
Epoch: 2. Loss: 2.297895669937134. Accuracy: 10
Epoch: 3. Loss: 2.3003079891204834. Accuracy: 10
Epoch: 4. Loss: 2.3107075691223145. Accuracy: 10
Epoch: 5. Loss: 2.306203603744507. Accuracy: 10
Epoch: 6. Loss: 2.3026938438415527. Accuracy: 10
Epoch: 7. Loss: 2.315995454788208. Accuracy: 10
Epoch: 8. Loss: 2.296825647354126. Accuracy: 10
Epoch: 9. Loss: 2.3147361278533936. Accuracy: 10
Epoch: 10. Loss: 2.3073644638061523. Accuracy: 10
Epoch: 11. Loss: 2.3762686252593994. Accuracy: 10
Epoch: 12. Loss: 2.3078365325927734. Accuracy: 10
Epoch: 13. Loss: 2.317976713180542. Accuracy: 10
Epoch: 14. Loss: 2.301936149597168. Accuracy: 10
[ 0.09107688132237185 256 tensor(10) ]
Loss: 2.301936149597168
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.0661145180094224

Epoch: 0. Loss: 0.684431791305542. Accuracy: 64
Epoch: 1. Loss: 2.3395259380340576. Accuracy: 10
Epoch: 2. Loss: 2.3245489597320557. Accuracy: 10
Epoch: 3. Loss: 2.2910263538360596. Accuracy: 10
Epoch: 4. Loss: 2.333078622817993. Accuracy: 10
Epoch: 5. Loss: 2.300551652908325. Accuracy: 10
Epoch: 6. Loss: 2.296389579772949. Accuracy: 10
Epoch: 7. Loss: 2.3216493129730225. Accuracy: 10
Epoch: 8. Loss: 2.297708749771118. Accuracy: 10
Epoch: 9. Loss: 2.327390432357788. Accuracy: 10
Epoch: 10. Loss: 2.333367109298706. Accuracy: 10
Epoch: 11. Loss: 2.298557758331299. Accuracy: 10
Epoch: 12. Loss: 2.2996864318847656. Accuracy: 10
Epoch: 13. Loss: 2.3312013149261475. Accuracy: 10
Epoch: 14. Loss: 2.29649019241333. Accuracy: 10
[ 0.0661145180094224 64 tensor(10) ]
Loss: 2.29649019241333
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.006115874818668628

Epoch: 0. Loss: 0.207483172416687. Accuracy: 85
Epoch: 1. Loss: 0.02880997210741043. Accuracy: 89
Epoch: 2. Loss: 0.10144571214914322. Accuracy: 89
Epoch: 3. Loss: 0.1638961136341095. Accuracy: 89
Epoch: 4. Loss: 0.09903337061405182. Accuracy: 90
Epoch: 5. Loss: 0.1797240674495697. Accuracy: 89
Epoch: 6. Loss: 0.07702666521072388. Accuracy: 90
Epoch: 7. Loss: 0.013732179999351501. Accuracy: 90
Epoch: 8. Loss: 0.008252114057540894. Accuracy: 91
Epoch: 9. Loss: 0.05692286789417267. Accuracy: 90
Epoch: 10. Loss: 0.1618003249168396. Accuracy: 90
Epoch: 11. Loss: 0.0002561807632446289. Accuracy: 90
Epoch: 12. Loss: 0.06094572693109512. Accuracy: 90
Epoch: 13. Loss: 0.029722869396209717. Accuracy: 91
Epoch: 14. Loss: 0.15756958723068237. Accuracy: 91
[ 0.006115874818668628 64 tensor(91) ]
Loss: 0.15756958723068237
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.004620921164670255

Epoch: 0. Loss: 0.302327036857605. Accuracy: 87
Epoch: 1. Loss: 0.027123771607875824. Accuracy: 89
Epoch: 2. Loss: 0.05111604183912277. Accuracy: 89
Epoch: 3. Loss: 0.22399215400218964. Accuracy: 90
Epoch: 4. Loss: 0.10665156692266464. Accuracy: 91
Epoch: 5. Loss: 0.0021319687366485596. Accuracy: 90
Epoch: 6. Loss: 0.005528092384338379. Accuracy: 91
Epoch: 7. Loss: 0.06697198748588562. Accuracy: 91
Epoch: 8. Loss: 0.010205477476119995. Accuracy: 91
Epoch: 9. Loss: 0.044250354170799255. Accuracy: 91
Epoch: 10. Loss: 0.06463398039340973. Accuracy: 91
Epoch: 11. Loss: 0.007949598133563995. Accuracy: 91
Epoch: 12. Loss: 0.03229522705078125. Accuracy: 91
Epoch: 13. Loss: 0.07626688480377197. Accuracy: 91
Epoch: 14. Loss: 0.05663381516933441. Accuracy: 91
[ 0.004620921164670255 64 tensor(91) ]
Loss: 0.05663381516933441
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.004780923538210548

Epoch: 0. Loss: 0.02228553593158722. Accuracy: 87
Epoch: 1. Loss: 0.0633971095085144. Accuracy: 89
Epoch: 2. Loss: 0.017269037663936615. Accuracy: 91
Epoch: 3. Loss: 0.008817464113235474. Accuracy: 91
Epoch: 4. Loss: 0.014701776206493378. Accuracy: 91
Epoch: 5. Loss: 0.11135922372341156. Accuracy: 91
Epoch: 6. Loss: 0.03418203443288803. Accuracy: 92
Epoch: 7. Loss: 0.07046838849782944. Accuracy: 91
Epoch: 8. Loss: 0.010406896471977234. Accuracy: 92
Epoch: 9. Loss: 0.08880999684333801. Accuracy: 92
Epoch: 10. Loss: 0.10933277755975723. Accuracy: 91
Epoch: 11. Loss: 0.0009353160858154297. Accuracy: 91
Epoch: 12. Loss: 0.018230661749839783. Accuracy: 92
Epoch: 13. Loss: 0.02247878909111023. Accuracy: 92
Epoch: 14. Loss: 0.03918573260307312. Accuracy: 91
[ 0.004780923538210548 64 tensor(91) ]
Loss: 0.03918573260307312
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.022055717497301945

Epoch: 0. Loss: 0.24214057624340057. Accuracy: 82
Epoch: 1. Loss: 0.11723444610834122. Accuracy: 83
Epoch: 2. Loss: 0.21967045962810516. Accuracy: 85
Epoch: 3. Loss: 0.11607978492975235. Accuracy: 86
Epoch: 4. Loss: 0.1562032401561737. Accuracy: 86
Epoch: 5. Loss: 0.07998345047235489. Accuracy: 86
Epoch: 6. Loss: 0.09034242480993271. Accuracy: 85
Epoch: 7. Loss: 0.34855079650878906. Accuracy: 86
Epoch: 8. Loss: 0.10394012928009033. Accuracy: 86
Epoch: 9. Loss: 0.3134225904941559. Accuracy: 86
Epoch: 10. Loss: 0.21750396490097046. Accuracy: 85
Epoch: 11. Loss: 0.13466869294643402. Accuracy: 85
Epoch: 12. Loss: 0.12232023477554321. Accuracy: 86
Epoch: 13. Loss: 0.13249659538269043. Accuracy: 85
Epoch: 14. Loss: 0.3726317584514618. Accuracy: 86
[ 0.022055717497301945 128 tensor(86) ]
Loss: 0.3726317584514618
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0052398566284714634

Epoch: 0. Loss: 0.045223645865917206. Accuracy: 87
Epoch: 1. Loss: 0.17510844767093658. Accuracy: 89
Epoch: 2. Loss: 0.32962164282798767. Accuracy: 89
Epoch: 3. Loss: 0.07932177186012268. Accuracy: 89
Epoch: 4. Loss: 0.15095002949237823. Accuracy: 90
Epoch: 5. Loss: 0.17754337191581726. Accuracy: 90
Epoch: 6. Loss: 0.06694691628217697. Accuracy: 90
Epoch: 7. Loss: 0.0638236254453659. Accuracy: 90
Epoch: 8. Loss: 0.12688452005386353. Accuracy: 91
Epoch: 9. Loss: 0.020625650882720947. Accuracy: 90
Epoch: 10. Loss: 0.1873430609703064. Accuracy: 90
Epoch: 11. Loss: 0.08765445649623871. Accuracy: 90
Epoch: 12. Loss: 0.03971712291240692. Accuracy: 90
Epoch: 13. Loss: 0.0111989825963974. Accuracy: 90
Epoch: 14. Loss: 0.2009718418121338. Accuracy: 90
[ 0.0052398566284714634 32 tensor(90) ]
Loss: 0.2009718418121338
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.04467297369834218

Epoch: 0. Loss: 0.741213321685791. Accuracy: 71
Epoch: 1. Loss: 0.6461014151573181. Accuracy: 74
Epoch: 2. Loss: 0.4971756637096405. Accuracy: 74
Epoch: 3. Loss: 0.4287397563457489. Accuracy: 75
Epoch: 4. Loss: 0.22474730014801025. Accuracy: 73
Epoch: 5. Loss: 0.3723442256450653. Accuracy: 74
Epoch: 6. Loss: 0.32507941126823425. Accuracy: 75
Epoch: 7. Loss: 0.3336484432220459. Accuracy: 74
Epoch: 8. Loss: 0.6228838562965393. Accuracy: 74
Epoch: 9. Loss: 0.4475127160549164. Accuracy: 74
Epoch: 10. Loss: 0.4560394287109375. Accuracy: 74
Epoch: 11. Loss: 0.33870768547058105. Accuracy: 76
Epoch: 12. Loss: 0.30598893761634827. Accuracy: 75
Epoch: 13. Loss: 0.25266167521476746. Accuracy: 75
Epoch: 14. Loss: 0.31983304023742676. Accuracy: 75
[ 0.04467297369834218 128 tensor(75) ]
Loss: 0.31983304023742676
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.007813275398330596

Epoch: 0. Loss: 0.4516541063785553. Accuracy: 78
Epoch: 1. Loss: 0.6343258619308472. Accuracy: 76
Epoch: 2. Loss: 0.2662593722343445. Accuracy: 80
Epoch: 3. Loss: 0.40486109256744385. Accuracy: 80
Epoch: 4. Loss: 0.20080986618995667. Accuracy: 79
Epoch: 5. Loss: 0.1076754480600357. Accuracy: 82
Epoch: 6. Loss: 0.16354818642139435. Accuracy: 81
Epoch: 7. Loss: 0.14175373315811157. Accuracy: 80
Epoch: 8. Loss: 0.42368218302726746. Accuracy: 80
Epoch: 9. Loss: 0.1325690895318985. Accuracy: 80
Epoch: 10. Loss: 0.15254060924053192. Accuracy: 80
Epoch: 11. Loss: 0.4327611029148102. Accuracy: 81
Epoch: 12. Loss: 0.3083016574382782. Accuracy: 81
Epoch: 13. Loss: 0.3620545566082001. Accuracy: 81
Epoch: 14. Loss: 0.4872688353061676. Accuracy: 81
[ 0.007813275398330596 32 tensor(81) ]
Loss: 0.4872688353061676
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.039007046399823136

Epoch: 0. Loss: 2.318154811859131. Accuracy: 10
Epoch: 1. Loss: 2.2962324619293213. Accuracy: 10
Epoch: 2. Loss: 2.3013598918914795. Accuracy: 10
Epoch: 3. Loss: 2.300938129425049. Accuracy: 10
Epoch: 4. Loss: 2.308837413787842. Accuracy: 10
Epoch: 5. Loss: 2.317885637283325. Accuracy: 10
Epoch: 6. Loss: 2.3008649349212646. Accuracy: 10
Epoch: 7. Loss: 2.321390390396118. Accuracy: 10
Epoch: 8. Loss: 2.302746295928955. Accuracy: 10
Epoch: 9. Loss: 2.3080670833587646. Accuracy: 10
Epoch: 10. Loss: 2.2988359928131104. Accuracy: 10
Epoch: 11. Loss: 2.30046010017395. Accuracy: 10
Epoch: 12. Loss: 2.302215814590454. Accuracy: 10
Epoch: 13. Loss: 2.299471139907837. Accuracy: 10
Epoch: 14. Loss: 2.3070507049560547. Accuracy: 10
[ 0.039007046399823136 128 tensor(10) ]
Loss: 2.3070507049560547
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.07160565219135374

Epoch: 0. Loss: 2.2601640224456787. Accuracy: 10
Epoch: 1. Loss: 2.2862942218780518. Accuracy: 10
Epoch: 2. Loss: 2.3025901317596436. Accuracy: 10
Epoch: 3. Loss: 2.28208589553833. Accuracy: 10
Epoch: 4. Loss: 2.3312320709228516. Accuracy: 10
Epoch: 5. Loss: 2.2908313274383545. Accuracy: 10
Epoch: 6. Loss: 2.2966084480285645. Accuracy: 10
Epoch: 7. Loss: 2.287665605545044. Accuracy: 10
Epoch: 8. Loss: 2.3472752571105957. Accuracy: 10
Epoch: 9. Loss: 2.3192131519317627. Accuracy: 10
Epoch: 10. Loss: 2.290743589401245. Accuracy: 10
Epoch: 11. Loss: 2.3165879249572754. Accuracy: 10
Epoch: 12. Loss: 2.3268890380859375. Accuracy: 10
Epoch: 13. Loss: 2.337062358856201. Accuracy: 10
Epoch: 14. Loss: 2.2754995822906494. Accuracy: 10
[ 0.07160565219135374 32 tensor(10) ]
Loss: 2.2754995822906494
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.0040161517892913

Epoch: 0. Loss: 0.3694586753845215. Accuracy: 87
Epoch: 1. Loss: 0.4672769606113434. Accuracy: 90
Epoch: 2. Loss: 0.06753234565258026. Accuracy: 91
Epoch: 3. Loss: 0.07920986413955688. Accuracy: 91
Epoch: 4. Loss: 0.044241972267627716. Accuracy: 91
Epoch: 5. Loss: 0.08395574986934662. Accuracy: 92
Epoch: 6. Loss: 0.005363687872886658. Accuracy: 91
Epoch: 7. Loss: 0.07584282010793686. Accuracy: 91
Epoch: 8. Loss: 0.015578493475914001. Accuracy: 91
Epoch: 9. Loss: 0.033421590924263. Accuracy: 91
Epoch: 10. Loss: 0.11449560523033142. Accuracy: 91
Epoch: 11. Loss: 0.0781194418668747. Accuracy: 91
Epoch: 12. Loss: 0.055865272879600525. Accuracy: 92
Epoch: 13. Loss: 0.13588528335094452. Accuracy: 91
Epoch: 14. Loss: 0.030919484794139862. Accuracy: 90
[ 0.0040161517892913 64 tensor(90) ]
Loss: 0.030919484794139862
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.07158181440937042

Epoch: 0. Loss: 1.1701151132583618. Accuracy: 51
Epoch: 1. Loss: 0.778709352016449. Accuracy: 52
Epoch: 2. Loss: 0.7543100714683533. Accuracy: 51
Epoch: 3. Loss: 1.2767932415008545. Accuracy: 55
Epoch: 4. Loss: 0.96489417552948. Accuracy: 55
Epoch: 5. Loss: 1.082727313041687. Accuracy: 57
Epoch: 6. Loss: 1.0920968055725098. Accuracy: 55
Epoch: 7. Loss: 0.8060311675071716. Accuracy: 54
Epoch: 8. Loss: 1.0193253755569458. Accuracy: 57
Epoch: 9. Loss: 0.6647350192070007. Accuracy: 57
Epoch: 10. Loss: 1.142815351486206. Accuracy: 56
Epoch: 11. Loss: 0.7485297918319702. Accuracy: 47
Epoch: 12. Loss: 1.0554808378219604. Accuracy: 57
Epoch: 13. Loss: 0.46495574712753296. Accuracy: 54
Epoch: 14. Loss: 0.7689520120620728. Accuracy: 55
[ 0.07158181440937042 64 tensor(55) ]
Loss: 0.7689520120620728
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.00387118817489729

Epoch: 0. Loss: 0.29253315925598145. Accuracy: 85
Epoch: 1. Loss: 0.08885704725980759. Accuracy: 89
Epoch: 2. Loss: 0.09051494300365448. Accuracy: 90
Epoch: 3. Loss: 0.06305086612701416. Accuracy: 92
Epoch: 4. Loss: 0.26802223920822144. Accuracy: 92
Epoch: 5. Loss: 0.04991694539785385. Accuracy: 91
Epoch: 6. Loss: 0.0963340550661087. Accuracy: 91
Epoch: 7. Loss: 0.021546363830566406. Accuracy: 92
Epoch: 8. Loss: 0.14799821376800537. Accuracy: 91
Epoch: 9. Loss: 0.6000615358352661. Accuracy: 92
Epoch: 10. Loss: 0.34213894605636597. Accuracy: 92
Epoch: 11. Loss: 0.03844979405403137. Accuracy: 91
Epoch: 12. Loss: 0.027329497039318085. Accuracy: 92
Epoch: 13. Loss: 0.07276314496994019. Accuracy: 93
Epoch: 14. Loss: 0.10049501061439514. Accuracy: 92
[ 0.00387118817489729 64 tensor(92) ]
Loss: 0.10049501061439514
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.003996663741509031

Epoch: 0. Loss: 0.1176401898264885. Accuracy: 86
Epoch: 1. Loss: 0.18658268451690674. Accuracy: 88
Epoch: 2. Loss: 0.013280026614665985. Accuracy: 90
Epoch: 3. Loss: 0.3897344768047333. Accuracy: 90
Epoch: 4. Loss: 0.006955668330192566. Accuracy: 91
Epoch: 5. Loss: 0.025419414043426514. Accuracy: 91
Epoch: 6. Loss: 0.025148101150989532. Accuracy: 91
Epoch: 7. Loss: 0.1521977186203003. Accuracy: 91
Epoch: 8. Loss: 0.004351094365119934. Accuracy: 91
Epoch: 9. Loss: 0.0023101866245269775. Accuracy: 92
Epoch: 10. Loss: 0.03821045160293579. Accuracy: 92
Epoch: 11. Loss: 0.015883654356002808. Accuracy: 91
Epoch: 12. Loss: 0.10573925077915192. Accuracy: 92
Epoch: 13. Loss: 0.020024195313453674. Accuracy: 92
Epoch: 14. Loss: 0.1866307109594345. Accuracy: 92
[ 0.003996663741509031 64 tensor(92) ]
Loss: 0.1866307109594345
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.02045835046075511

Epoch: 0. Loss: 0.3728295564651489. Accuracy: 77
Epoch: 1. Loss: 0.5704662799835205. Accuracy: 73
Epoch: 2. Loss: 0.5061571002006531. Accuracy: 76
Epoch: 3. Loss: 0.5613809823989868. Accuracy: 78
Epoch: 4. Loss: 0.25028663873672485. Accuracy: 78
Epoch: 5. Loss: 0.12386016547679901. Accuracy: 79
Epoch: 6. Loss: 0.3705862760543823. Accuracy: 78
Epoch: 7. Loss: 0.41418927907943726. Accuracy: 80
Epoch: 8. Loss: 0.33958810567855835. Accuracy: 80
Epoch: 9. Loss: 0.25857335329055786. Accuracy: 77
Epoch: 10. Loss: 0.44865846633911133. Accuracy: 79
Epoch: 11. Loss: 0.132100909948349. Accuracy: 79
Epoch: 12. Loss: 0.11412365734577179. Accuracy: 79
Epoch: 13. Loss: 0.43317899107933044. Accuracy: 78
Epoch: 14. Loss: 0.3040544390678406. Accuracy: 78
[ 0.02045835046075511 64 tensor(78) ]
Loss: 0.3040544390678406
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.00530279678993381

Epoch: 0. Loss: 0.1754077821969986. Accuracy: 85
Epoch: 1. Loss: 0.2620197534561157. Accuracy: 88
Epoch: 2. Loss: 0.16982562839984894. Accuracy: 89
Epoch: 3. Loss: 0.11074867099523544. Accuracy: 90
Epoch: 4. Loss: 0.06693834066390991. Accuracy: 90
Epoch: 5. Loss: 0.08037256449460983. Accuracy: 91
Epoch: 6. Loss: 0.08215739578008652. Accuracy: 91
Epoch: 7. Loss: 0.03188095614314079. Accuracy: 91
Epoch: 8. Loss: 0.1486349105834961. Accuracy: 90
Epoch: 9. Loss: 0.054327692836523056. Accuracy: 91
Epoch: 10. Loss: 0.00886001717299223. Accuracy: 92
Epoch: 11. Loss: 0.12372893840074539. Accuracy: 91
Epoch: 12. Loss: 0.24272383749485016. Accuracy: 92
Epoch: 13. Loss: 0.06300361454486847. Accuracy: 91
Epoch: 14. Loss: 0.02215200662612915. Accuracy: 91
[ 0.00530279678993381 128 tensor(91) ]
Loss: 0.02215200662612915
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.010094813363570154

Epoch: 0. Loss: 0.17782627046108246. Accuracy: 83
Epoch: 1. Loss: 0.17675574123859406. Accuracy: 88
Epoch: 2. Loss: 0.15007184445858002. Accuracy: 89
Epoch: 3. Loss: 0.08412149548530579. Accuracy: 90
Epoch: 4. Loss: 0.08798033744096756. Accuracy: 90
Epoch: 5. Loss: 0.08286691457033157. Accuracy: 90
Epoch: 6. Loss: 0.11726779490709305. Accuracy: 91
Epoch: 7. Loss: 0.04394519701600075. Accuracy: 90
Epoch: 8. Loss: 0.08041401952505112. Accuracy: 91
Epoch: 9. Loss: 0.09868878871202469. Accuracy: 91
Epoch: 10. Loss: 0.06032971665263176. Accuracy: 91
Epoch: 11. Loss: 0.07679114490747452. Accuracy: 91
Epoch: 12. Loss: 0.10850387066602707. Accuracy: 91
Epoch: 13. Loss: 0.016806533560156822. Accuracy: 90
Epoch: 14. Loss: 0.07801658660173416. Accuracy: 90
[ 0.010094813363570154 256 tensor(90) ]
Loss: 0.07801658660173416
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.00164737400693779

Epoch: 0. Loss: 0.26952770352363586. Accuracy: 77
Epoch: 1. Loss: 0.27507326006889343. Accuracy: 82
Epoch: 2. Loss: 0.21226443350315094. Accuracy: 85
Epoch: 3. Loss: 0.2169392853975296. Accuracy: 88
Epoch: 4. Loss: 0.11187630891799927. Accuracy: 88
Epoch: 5. Loss: 0.24024049937725067. Accuracy: 89
Epoch: 6. Loss: 0.03732634708285332. Accuracy: 90
Epoch: 7. Loss: 0.2426704317331314. Accuracy: 90
Epoch: 8. Loss: 0.08081229776144028. Accuracy: 91
Epoch: 9. Loss: 0.04974331334233284. Accuracy: 91
Epoch: 10. Loss: 0.2072031944990158. Accuracy: 91
Epoch: 11. Loss: 0.04127909988164902. Accuracy: 91
Epoch: 12. Loss: 0.04275916889309883. Accuracy: 91
Epoch: 13. Loss: 0.13506583869457245. Accuracy: 91
Epoch: 14. Loss: 0.061558712273836136. Accuracy: 91
[ 0.00164737400693779 256 tensor(91) ]
Loss: 0.061558712273836136
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.09682755898487905

Epoch: 0. Loss: 0.7250474095344543. Accuracy: 59
Epoch: 1. Loss: 0.8292801380157471. Accuracy: 62
Epoch: 2. Loss: 0.9519805312156677. Accuracy: 58
Epoch: 3. Loss: 0.7936813235282898. Accuracy: 59
Epoch: 4. Loss: 0.8797248005867004. Accuracy: 63
Epoch: 5. Loss: 0.7260129451751709. Accuracy: 61
Epoch: 6. Loss: 0.8234119415283203. Accuracy: 58
Epoch: 7. Loss: 0.7452226281166077. Accuracy: 63
Epoch: 8. Loss: 0.7028420567512512. Accuracy: 62
Epoch: 9. Loss: 0.6765387654304504. Accuracy: 61
Epoch: 10. Loss: 0.8091655373573303. Accuracy: 63
Epoch: 11. Loss: 0.749488890171051. Accuracy: 62
Epoch: 12. Loss: 2.324725389480591. Accuracy: 10
Epoch: 13. Loss: 2.307072639465332. Accuracy: 10
Epoch: 14. Loss: 2.304429769515991. Accuracy: 10
[ 0.09682755898487905 128 tensor(10) ]
Loss: 2.304429769515991
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.03197907112470092

Epoch: 0. Loss: 0.7483580708503723. Accuracy: 65
Epoch: 1. Loss: 0.5401660203933716. Accuracy: 68
Epoch: 2. Loss: 0.5800732374191284. Accuracy: 68
Epoch: 3. Loss: 0.4831330478191376. Accuracy: 70
Epoch: 4. Loss: 0.6914002895355225. Accuracy: 70
Epoch: 5. Loss: 0.41943058371543884. Accuracy: 70
Epoch: 6. Loss: 0.5351483821868896. Accuracy: 71
Epoch: 7. Loss: 0.6366919875144958. Accuracy: 72
Epoch: 8. Loss: 0.6004716753959656. Accuracy: 70
Epoch: 9. Loss: 0.6008502840995789. Accuracy: 71
Epoch: 10. Loss: 0.5247058868408203. Accuracy: 71
Epoch: 11. Loss: 0.5453450083732605. Accuracy: 70
Epoch: 12. Loss: 0.5459715127944946. Accuracy: 71
Epoch: 13. Loss: 0.5365076661109924. Accuracy: 70
Epoch: 14. Loss: 0.33625519275665283. Accuracy: 68
[ 0.03197907112470092 128 tensor(68) ]
Loss: 0.33625519275665283
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.006736722669626273

Epoch: 0. Loss: 0.2299363762140274. Accuracy: 86
Epoch: 1. Loss: 0.1081714928150177. Accuracy: 89
Epoch: 2. Loss: 0.1021406427025795. Accuracy: 90
Epoch: 3. Loss: 0.12346184253692627. Accuracy: 89
Epoch: 4. Loss: 0.18625293672084808. Accuracy: 91
Epoch: 5. Loss: 0.1800161600112915. Accuracy: 91
Epoch: 6. Loss: 0.21032731235027313. Accuracy: 91
Epoch: 7. Loss: 0.05242926999926567. Accuracy: 91
Epoch: 8. Loss: 0.026177221909165382. Accuracy: 91
Epoch: 9. Loss: 0.12799496948719025. Accuracy: 91
Epoch: 10. Loss: 0.15036232769489288. Accuracy: 92
Epoch: 11. Loss: 0.03313243016600609. Accuracy: 91
Epoch: 12. Loss: 0.06022334098815918. Accuracy: 91
Epoch: 13. Loss: 0.04531428590416908. Accuracy: 91
Epoch: 14. Loss: 0.14077876508235931. Accuracy: 91
[ 0.006736722669626273 128 tensor(91) ]
Loss: 0.14077876508235931
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.04702536595488104

Epoch: 0. Loss: 1.022370457649231. Accuracy: 56
Epoch: 1. Loss: 1.0548228025436401. Accuracy: 58
Epoch: 2. Loss: 0.8176287412643433. Accuracy: 58
Epoch: 3. Loss: 1.1994211673736572. Accuracy: 57
Epoch: 4. Loss: 1.100804090499878. Accuracy: 58
Epoch: 5. Loss: 0.8815345764160156. Accuracy: 59
Epoch: 6. Loss: 1.2565276622772217. Accuracy: 56
Epoch: 7. Loss: 0.6049343347549438. Accuracy: 56
Epoch: 8. Loss: 1.049301266670227. Accuracy: 57
Epoch: 9. Loss: 0.853013277053833. Accuracy: 57
Epoch: 10. Loss: 1.0671343803405762. Accuracy: 57
Epoch: 11. Loss: 0.5065249800682068. Accuracy: 57
Epoch: 12. Loss: 0.6291508078575134. Accuracy: 55
Epoch: 13. Loss: 0.8336650133132935. Accuracy: 55
Epoch: 14. Loss: 1.0017364025115967. Accuracy: 55
[ 0.04702536595488104 64 tensor(55) ]
Loss: 1.0017364025115967
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.004106905707916243

Epoch: 0. Loss: 0.5266622304916382. Accuracy: 87
Epoch: 1. Loss: 0.03582417964935303. Accuracy: 90
Epoch: 2. Loss: 0.1371130645275116. Accuracy: 90
Epoch: 3. Loss: 0.18399259448051453. Accuracy: 91
Epoch: 4. Loss: 0.16324461996555328. Accuracy: 92
Epoch: 5. Loss: 0.17298853397369385. Accuracy: 91
Epoch: 6. Loss: 0.00692218542098999. Accuracy: 92
Epoch: 7. Loss: 0.007285743951797485. Accuracy: 90
Epoch: 8. Loss: 0.10577397793531418. Accuracy: 92
Epoch: 9. Loss: 0.0242929607629776. Accuracy: 92
Epoch: 10. Loss: 0.006599202752113342. Accuracy: 91
Epoch: 11. Loss: 0.00939612090587616. Accuracy: 92
Epoch: 12. Loss: 0.03410705178976059. Accuracy: 91
Epoch: 13. Loss: 0.15102878212928772. Accuracy: 92
Epoch: 14. Loss: 0.039434537291526794. Accuracy: 92
[ 0.004106905707916243 64 tensor(92) ]
Loss: 0.039434537291526794
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.004342807013462147

Epoch: 0. Loss: 0.13464482128620148. Accuracy: 86
Epoch: 1. Loss: 0.1722511202096939. Accuracy: 88
Epoch: 2. Loss: 0.28518927097320557. Accuracy: 89
Epoch: 3. Loss: 0.19601310789585114. Accuracy: 90
Epoch: 4. Loss: 0.2569006085395813. Accuracy: 90
Epoch: 5. Loss: 0.21124546229839325. Accuracy: 90
Epoch: 6. Loss: 0.13092249631881714. Accuracy: 90
Epoch: 7. Loss: 0.029065623879432678. Accuracy: 90
Epoch: 8. Loss: 0.47126302123069763. Accuracy: 91
Epoch: 9. Loss: 0.2420443296432495. Accuracy: 91
Epoch: 10. Loss: 0.015137940645217896. Accuracy: 91
Epoch: 11. Loss: 0.12737230956554413. Accuracy: 90
Epoch: 12. Loss: 0.023961439728736877. Accuracy: 91
Epoch: 13. Loss: 0.048319414258003235. Accuracy: 91
Epoch: 14. Loss: 0.027628540992736816. Accuracy: 91
[ 0.004342807013462147 64 tensor(91) ]
Loss: 0.027628540992736816
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.00975484626134905

Epoch: 0. Loss: 0.2315947413444519. Accuracy: 82
Epoch: 1. Loss: 0.07579232007265091. Accuracy: 87
Epoch: 2. Loss: 0.1238674521446228. Accuracy: 88
Epoch: 3. Loss: 0.14387349784374237. Accuracy: 89
Epoch: 4. Loss: 0.18778562545776367. Accuracy: 90
Epoch: 5. Loss: 0.051922012120485306. Accuracy: 88
Epoch: 6. Loss: 0.11586934328079224. Accuracy: 91
Epoch: 7. Loss: 0.07389573007822037. Accuracy: 90
Epoch: 8. Loss: 0.0855030044913292. Accuracy: 90
Epoch: 9. Loss: 0.08702889829874039. Accuracy: 90
Epoch: 10. Loss: 0.22126583755016327. Accuracy: 89
Epoch: 11. Loss: 0.10542770475149155. Accuracy: 90
Epoch: 12. Loss: 0.04739637300372124. Accuracy: 91
Epoch: 13. Loss: 0.07071992754936218. Accuracy: 91
Epoch: 14. Loss: 0.16157667338848114. Accuracy: 89
[ 0.00975484626134905 256 tensor(89) ]
Loss: 0.16157667338848114
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.009965542887106974

Epoch: 0. Loss: 0.18088333308696747. Accuracy: 85
Epoch: 1. Loss: 0.028377866372466087. Accuracy: 89
Epoch: 2. Loss: 0.1046217754483223. Accuracy: 89
Epoch: 3. Loss: 0.10116223245859146. Accuracy: 90
Epoch: 4. Loss: 0.22825407981872559. Accuracy: 90
Epoch: 5. Loss: 0.08804398775100708. Accuracy: 91
Epoch: 6. Loss: 0.05353698506951332. Accuracy: 91
Epoch: 7. Loss: 0.05148296058177948. Accuracy: 91
Epoch: 8. Loss: 0.24528072774410248. Accuracy: 91
Epoch: 9. Loss: 0.12571869790554047. Accuracy: 92
Epoch: 10. Loss: 0.03376835212111473. Accuracy: 91
Epoch: 11. Loss: 0.11755899339914322. Accuracy: 91
Epoch: 12. Loss: 0.035076115280389786. Accuracy: 91
Epoch: 13. Loss: 0.02137591503560543. Accuracy: 91
Epoch: 14. Loss: 0.07712703198194504. Accuracy: 91
[ 0.009965542887106974 256 tensor(91) ]
Loss: 0.07712703198194504
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.034316299210708716

Epoch: 0. Loss: 2.3030991554260254. Accuracy: 10
Epoch: 1. Loss: 2.30534291267395. Accuracy: 10
Epoch: 2. Loss: 2.303781747817993. Accuracy: 10
Epoch: 3. Loss: 2.307828903198242. Accuracy: 10
Epoch: 4. Loss: 2.30466628074646. Accuracy: 10
Epoch: 5. Loss: 2.30867600440979. Accuracy: 10
Epoch: 6. Loss: 2.301008701324463. Accuracy: 10
Epoch: 7. Loss: 2.2961983680725098. Accuracy: 10
Epoch: 8. Loss: 2.30757212638855. Accuracy: 10
Epoch: 9. Loss: 0.8752002120018005. Accuracy: 57
Epoch: 10. Loss: 0.7713345885276794. Accuracy: 58
Epoch: 11. Loss: 0.8183034062385559. Accuracy: 59
Epoch: 12. Loss: 0.7223758697509766. Accuracy: 59
Epoch: 13. Loss: 0.8229724764823914. Accuracy: 58
Epoch: 14. Loss: 0.936664342880249. Accuracy: 59
[ 0.034316299210708716 256 tensor(59) ]
Loss: 0.936664342880249
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.004291820869190705

Epoch: 0. Loss: 0.20288681983947754. Accuracy: 85
Epoch: 1. Loss: 0.09837808459997177. Accuracy: 88
Epoch: 2. Loss: 0.05846114084124565. Accuracy: 90
Epoch: 3. Loss: 0.06479616463184357. Accuracy: 90
Epoch: 4. Loss: 0.11973437666893005. Accuracy: 90
Epoch: 5. Loss: 0.08764825016260147. Accuracy: 91
Epoch: 6. Loss: 0.04869601130485535. Accuracy: 91
Epoch: 7. Loss: 0.06178462877869606. Accuracy: 92
Epoch: 8. Loss: 0.07111264765262604. Accuracy: 91
Epoch: 9. Loss: 0.06267788261175156. Accuracy: 91
Epoch: 10. Loss: 0.08687249571084976. Accuracy: 91
Epoch: 11. Loss: 0.04625688120722771. Accuracy: 91
Epoch: 12. Loss: 0.025696968659758568. Accuracy: 92
Epoch: 13. Loss: 0.07029511779546738. Accuracy: 91
Epoch: 14. Loss: 0.03816215693950653. Accuracy: 91
[ 0.004291820869190705 128 tensor(91) ]
Loss: 0.03816215693950653
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.0011806187781386696

Epoch: 0. Loss: 0.33924487233161926. Accuracy: 78
Epoch: 1. Loss: 0.3492110073566437. Accuracy: 82
Epoch: 2. Loss: 0.18182273209095. Accuracy: 85
Epoch: 3. Loss: 0.14823392033576965. Accuracy: 87
Epoch: 4. Loss: 0.10820933431386948. Accuracy: 88
Epoch: 5. Loss: 0.12444452196359634. Accuracy: 89
Epoch: 6. Loss: 0.17765282094478607. Accuracy: 90
Epoch: 7. Loss: 0.061289384961128235. Accuracy: 90
Epoch: 8. Loss: 0.08034435659646988. Accuracy: 90
Epoch: 9. Loss: 0.12163569778203964. Accuracy: 90
Epoch: 10. Loss: 0.054121751338243484. Accuracy: 90
Epoch: 11. Loss: 0.0865001380443573. Accuracy: 89
Epoch: 12. Loss: 0.0639399066567421. Accuracy: 91
Epoch: 13. Loss: 0.14413295686244965. Accuracy: 90
Epoch: 14. Loss: 0.11785504221916199. Accuracy: 90
[ 0.0011806187781386696 128 tensor(90) ]
Loss: 0.11785504221916199
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.0023181682154915398

Epoch: 0. Loss: 0.3120913803577423. Accuracy: 83
Epoch: 1. Loss: 0.09096142649650574. Accuracy: 87
Epoch: 2. Loss: 0.11987883597612381. Accuracy: 88
Epoch: 3. Loss: 0.1045476421713829. Accuracy: 89
Epoch: 4. Loss: 0.10407090187072754. Accuracy: 90
Epoch: 5. Loss: 0.1203153133392334. Accuracy: 90
Epoch: 6. Loss: 0.08827421814203262. Accuracy: 90
Epoch: 7. Loss: 0.006258437875658274. Accuracy: 91
Epoch: 8. Loss: 0.06254132837057114. Accuracy: 90
Epoch: 9. Loss: 0.1139693632721901. Accuracy: 91
Epoch: 10. Loss: 0.027802234515547752. Accuracy: 91
Epoch: 11. Loss: 0.05544140562415123. Accuracy: 91
Epoch: 12. Loss: 0.04365750774741173. Accuracy: 91
Epoch: 13. Loss: 0.026738366112113. Accuracy: 91
Epoch: 14. Loss: 0.09104391187429428. Accuracy: 92
[ 0.0023181682154915398 128 tensor(92) ]
Loss: 0.09104391187429428
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0037757641112426484

Epoch: 0. Loss: 0.1542816460132599. Accuracy: 88
Epoch: 1. Loss: 0.22999827563762665. Accuracy: 89
Epoch: 2. Loss: 0.14873020350933075. Accuracy: 90
Epoch: 3. Loss: 0.1822565793991089. Accuracy: 91
Epoch: 4. Loss: 0.13902534544467926. Accuracy: 91
Epoch: 5. Loss: 0.2516445219516754. Accuracy: 91
Epoch: 6. Loss: 0.017066165804862976. Accuracy: 91
Epoch: 7. Loss: 0.019921571016311646. Accuracy: 92
Epoch: 8. Loss: 0.07397165149450302. Accuracy: 91
Epoch: 9. Loss: 0.05913257226347923. Accuracy: 91
Epoch: 10. Loss: 0.14026875793933868. Accuracy: 91
Epoch: 11. Loss: 0.003946945071220398. Accuracy: 92
Epoch: 12. Loss: 0.023942552506923676. Accuracy: 91
Epoch: 13. Loss: 0.18538692593574524. Accuracy: 91
Epoch: 14. Loss: 0.20340409874916077. Accuracy: 91
[ 0.0037757641112426484 32 tensor(91) ]
Loss: 0.20340409874916077
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.06555329763138208

Epoch: 0. Loss: 1.1795923709869385. Accuracy: 56
Epoch: 1. Loss: 0.9223531484603882. Accuracy: 50
Epoch: 2. Loss: 0.7540009021759033. Accuracy: 57
Epoch: 3. Loss: 1.0283536911010742. Accuracy: 56
Epoch: 4. Loss: 0.7670051455497742. Accuracy: 55
Epoch: 5. Loss: 0.8914636373519897. Accuracy: 55
Epoch: 6. Loss: 1.0261073112487793. Accuracy: 53
Epoch: 7. Loss: 1.1140527725219727. Accuracy: 54
Epoch: 8. Loss: 0.8130151033401489. Accuracy: 55
Epoch: 9. Loss: 0.7961987257003784. Accuracy: 57
Epoch: 10. Loss: 0.7850943803787231. Accuracy: 54
Epoch: 11. Loss: 0.8511357307434082. Accuracy: 55
Epoch: 12. Loss: 0.9843082427978516. Accuracy: 56
Epoch: 13. Loss: 1.206527590751648. Accuracy: 55
Epoch: 14. Loss: 0.9530565142631531. Accuracy: 55
[ 0.06555329763138208 64 tensor(55) ]
Loss: 0.9530565142631531
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.07888498006427777

Epoch: 0. Loss: 2.3293166160583496. Accuracy: 10
Epoch: 1. Loss: 2.3180902004241943. Accuracy: 10
Epoch: 2. Loss: 2.3551952838897705. Accuracy: 10
Epoch: 3. Loss: 2.3010826110839844. Accuracy: 10
Epoch: 4. Loss: 2.3412234783172607. Accuracy: 10
Epoch: 5. Loss: 2.3228421211242676. Accuracy: 10
Epoch: 6. Loss: 2.3030223846435547. Accuracy: 10
Epoch: 7. Loss: 2.3246028423309326. Accuracy: 10
Epoch: 8. Loss: 2.318380832672119. Accuracy: 10
Epoch: 9. Loss: 2.338629722595215. Accuracy: 10
Epoch: 10. Loss: 2.268789291381836. Accuracy: 10
Epoch: 11. Loss: 2.272540807723999. Accuracy: 10
Epoch: 12. Loss: 2.3051817417144775. Accuracy: 10
Epoch: 13. Loss: 2.2894303798675537. Accuracy: 10
Epoch: 14. Loss: 2.3027076721191406. Accuracy: 10
[ 0.07888498006427777 32 tensor(10) ]
Loss: 2.3027076721191406
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.09993706489120896

Epoch: 0. Loss: 0.8579062223434448. Accuracy: 44
Epoch: 1. Loss: 1.1212786436080933. Accuracy: 50
Epoch: 2. Loss: 1.0555425882339478. Accuracy: 53
Epoch: 3. Loss: 1.4302241802215576. Accuracy: 20
Epoch: 4. Loss: 0.9192907810211182. Accuracy: 53
Epoch: 5. Loss: 1.0687148571014404. Accuracy: 50
Epoch: 6. Loss: 2.3594298362731934. Accuracy: 10
Epoch: 7. Loss: 2.3343307971954346. Accuracy: 10
Epoch: 8. Loss: 2.2922651767730713. Accuracy: 10
Epoch: 9. Loss: 2.3082664012908936. Accuracy: 10
Epoch: 10. Loss: 2.2971394062042236. Accuracy: 10
Epoch: 11. Loss: 2.270270586013794. Accuracy: 10
Epoch: 12. Loss: 2.321373224258423. Accuracy: 10
Epoch: 13. Loss: 2.3286690711975098. Accuracy: 10
Epoch: 14. Loss: 2.3065366744995117. Accuracy: 10
[ 0.09993706489120896 32 tensor(10) ]
Loss: 2.3065366744995117
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.06630585300882587

Epoch: 0. Loss: 2.298501491546631. Accuracy: 10
Epoch: 1. Loss: 2.3049516677856445. Accuracy: 10
Epoch: 2. Loss: 2.2944729328155518. Accuracy: 10
Epoch: 3. Loss: 2.3440797328948975. Accuracy: 10
Epoch: 4. Loss: 2.299173355102539. Accuracy: 10
Epoch: 5. Loss: 2.31972074508667. Accuracy: 10
Epoch: 6. Loss: 2.3435990810394287. Accuracy: 10
Epoch: 7. Loss: 2.3159124851226807. Accuracy: 10
Epoch: 8. Loss: 2.276223659515381. Accuracy: 10
Epoch: 9. Loss: 2.3226351737976074. Accuracy: 10
Epoch: 10. Loss: 2.341157913208008. Accuracy: 10
Epoch: 11. Loss: 2.2998266220092773. Accuracy: 10
Epoch: 12. Loss: 2.3176751136779785. Accuracy: 10
Epoch: 13. Loss: 2.2647712230682373. Accuracy: 10
Epoch: 14. Loss: 2.314458131790161. Accuracy: 10
[ 0.06630585300882587 32 tensor(10) ]
Loss: 2.314458131790161
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.005276379903492539

Epoch: 0. Loss: 0.23827853798866272. Accuracy: 87
Epoch: 1. Loss: 0.027732424437999725. Accuracy: 89
Epoch: 2. Loss: 0.06738127768039703. Accuracy: 89
Epoch: 3. Loss: 0.0026183128356933594. Accuracy: 90
Epoch: 4. Loss: 0.13355715572834015. Accuracy: 90
Epoch: 5. Loss: 0.009475663304328918. Accuracy: 91
Epoch: 6. Loss: 0.2533626854419708. Accuracy: 91
Epoch: 7. Loss: 0.10170484334230423. Accuracy: 91
Epoch: 8. Loss: 0.021136894822120667. Accuracy: 91
Epoch: 9. Loss: 0.006504133343696594. Accuracy: 91
Epoch: 10. Loss: 0.23651066422462463. Accuracy: 91
Epoch: 11. Loss: 0.007370665669441223. Accuracy: 91
Epoch: 12. Loss: 0.014244906604290009. Accuracy: 91
Epoch: 13. Loss: 0.017682597041130066. Accuracy: 91
Epoch: 14. Loss: 0.01681683212518692. Accuracy: 91
[ 0.005276379903492539 64 tensor(91) ]
Loss: 0.01681683212518692
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.0037898853820745792

Epoch: 0. Loss: 0.05581209063529968. Accuracy: 87
Epoch: 1. Loss: 0.20431312918663025. Accuracy: 90
Epoch: 2. Loss: 0.08959325402975082. Accuracy: 91
Epoch: 3. Loss: 0.1416594386100769. Accuracy: 90
Epoch: 4. Loss: 0.005310341715812683. Accuracy: 91
Epoch: 5. Loss: 0.0341719314455986. Accuracy: 91
Epoch: 6. Loss: 0.020255744457244873. Accuracy: 92
Epoch: 7. Loss: 0.0033434927463531494. Accuracy: 91
Epoch: 8. Loss: 0.022620901465415955. Accuracy: 91
Epoch: 9. Loss: 0.03819941729307175. Accuracy: 91
Epoch: 10. Loss: 0.0573689267039299. Accuracy: 91
Epoch: 11. Loss: 0.167718306183815. Accuracy: 91
Epoch: 12. Loss: 0.002840861678123474. Accuracy: 91
Epoch: 13. Loss: 0.23642632365226746. Accuracy: 92
Epoch: 14. Loss: 0.04355940967798233. Accuracy: 92
[ 0.0037898853820745792 64 tensor(92) ]
Loss: 0.04355940967798233
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.04221816860120781

Epoch: 0. Loss: 1.2074339389801025. Accuracy: 56
Epoch: 1. Loss: 0.8933966159820557. Accuracy: 58
Epoch: 2. Loss: 0.9214001297950745. Accuracy: 59
Epoch: 3. Loss: 0.6497461199760437. Accuracy: 59
Epoch: 4. Loss: 0.6943833827972412. Accuracy: 59
Epoch: 5. Loss: 1.0263599157333374. Accuracy: 58
Epoch: 6. Loss: 0.9174096584320068. Accuracy: 60
Epoch: 7. Loss: 0.4730171263217926. Accuracy: 58
Epoch: 8. Loss: 0.7274698615074158. Accuracy: 58
Epoch: 9. Loss: 1.0233112573623657. Accuracy: 59
Epoch: 10. Loss: 0.5688158869743347. Accuracy: 59
Epoch: 11. Loss: 0.4275079369544983. Accuracy: 56
Epoch: 12. Loss: 0.9804661273956299. Accuracy: 58
Epoch: 13. Loss: 0.8169019222259521. Accuracy: 59
Epoch: 14. Loss: 1.0070319175720215. Accuracy: 57
[ 0.04221816860120781 64 tensor(57) ]
Loss: 1.0070319175720215
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.001142550526119371

Epoch: 0. Loss: 0.2454649806022644. Accuracy: 84
Epoch: 1. Loss: 0.39452308416366577. Accuracy: 87
Epoch: 2. Loss: 0.1117473691701889. Accuracy: 87
Epoch: 3. Loss: 0.319650799036026. Accuracy: 89
Epoch: 4. Loss: 0.04057623818516731. Accuracy: 90
Epoch: 5. Loss: 0.038661763072013855. Accuracy: 89
Epoch: 6. Loss: 0.14405499398708344. Accuracy: 90
Epoch: 7. Loss: 0.026280872523784637. Accuracy: 91
Epoch: 8. Loss: 0.027321677654981613. Accuracy: 90
Epoch: 9. Loss: 0.1444072276353836. Accuracy: 91
Epoch: 10. Loss: 0.071475088596344. Accuracy: 90
Epoch: 11. Loss: 0.09884724766016006. Accuracy: 91
Epoch: 12. Loss: 0.027949176728725433. Accuracy: 91
Epoch: 13. Loss: 0.0898183062672615. Accuracy: 91
Epoch: 14. Loss: 0.03702902793884277. Accuracy: 91
[ 0.001142550526119371 32 tensor(91) ]
Loss: 0.03702902793884277
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.0037004548425344443

Epoch: 0. Loss: 0.1131291389465332. Accuracy: 83
Epoch: 1. Loss: 0.2317548543214798. Accuracy: 88
Epoch: 2. Loss: 0.13489477336406708. Accuracy: 89
Epoch: 3. Loss: 0.027952002361416817. Accuracy: 90
Epoch: 4. Loss: 0.1305052489042282. Accuracy: 91
Epoch: 5. Loss: 0.020475396886467934. Accuracy: 91
Epoch: 6. Loss: 0.14759190380573273. Accuracy: 91
Epoch: 7. Loss: 0.10238730907440186. Accuracy: 92
Epoch: 8. Loss: 0.04160529747605324. Accuracy: 91
Epoch: 9. Loss: 0.04847109317779541. Accuracy: 92
Epoch: 10. Loss: 0.043449949473142624. Accuracy: 92
Epoch: 11. Loss: 0.024370431900024414. Accuracy: 92
Epoch: 12. Loss: 0.07444057613611221. Accuracy: 92
Epoch: 13. Loss: 0.049450770020484924. Accuracy: 92
Epoch: 14. Loss: 0.061643946915864944. Accuracy: 92
[ 0.0037004548425344443 256 tensor(92) ]
Loss: 0.061643946915864944
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.02176438180497559

Epoch: 0. Loss: 0.626893937587738. Accuracy: 68
Epoch: 1. Loss: 0.4973343312740326. Accuracy: 70
Epoch: 2. Loss: 0.4564324915409088. Accuracy: 72
Epoch: 3. Loss: 0.5482322573661804. Accuracy: 72
Epoch: 4. Loss: 0.41243791580200195. Accuracy: 71
Epoch: 5. Loss: 0.44686007499694824. Accuracy: 71
Epoch: 6. Loss: 0.5208681225776672. Accuracy: 71
Epoch: 7. Loss: 0.4482887089252472. Accuracy: 72
Epoch: 8. Loss: 0.5823242664337158. Accuracy: 72
Epoch: 9. Loss: 0.680100679397583. Accuracy: 71
Epoch: 10. Loss: 0.3382277488708496. Accuracy: 73
Epoch: 11. Loss: 0.517162024974823. Accuracy: 73
Epoch: 12. Loss: 0.32378342747688293. Accuracy: 72
Epoch: 13. Loss: 0.5741789937019348. Accuracy: 72
Epoch: 14. Loss: 0.3819064199924469. Accuracy: 72
[ 0.02176438180497559 128 tensor(72) ]
Loss: 0.3819064199924469
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.011165396578755094

Epoch: 0. Loss: 0.12812049686908722. Accuracy: 86
Epoch: 1. Loss: 0.1665673404932022. Accuracy: 88
Epoch: 2. Loss: 0.33941328525543213. Accuracy: 88
Epoch: 3. Loss: 0.05753342807292938. Accuracy: 89
Epoch: 4. Loss: 0.227166548371315. Accuracy: 88
Epoch: 5. Loss: 0.11794835329055786. Accuracy: 89
Epoch: 6. Loss: 0.0910082459449768. Accuracy: 89
Epoch: 7. Loss: 0.12776406109333038. Accuracy: 89
Epoch: 8. Loss: 0.12105629593133926. Accuracy: 89
Epoch: 9. Loss: 0.15069322288036346. Accuracy: 89
Epoch: 10. Loss: 0.053406406193971634. Accuracy: 89
Epoch: 11. Loss: 0.1874569058418274. Accuracy: 90
Epoch: 12. Loss: 0.07473962008953094. Accuracy: 90
Epoch: 13. Loss: 0.08216556161642075. Accuracy: 89
Epoch: 14. Loss: 0.13883741199970245. Accuracy: 89
[ 0.011165396578755094 128 tensor(89) ]
Loss: 0.13883741199970245
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.05399592392639796

Epoch: 0. Loss: 2.291672706604004. Accuracy: 10
Epoch: 1. Loss: 2.3119430541992188. Accuracy: 10
Epoch: 2. Loss: 2.303899049758911. Accuracy: 10
Epoch: 3. Loss: 2.301771640777588. Accuracy: 10
Epoch: 4. Loss: 2.2984580993652344. Accuracy: 10
Epoch: 5. Loss: 2.311767816543579. Accuracy: 10
Epoch: 6. Loss: 2.295419931411743. Accuracy: 10
Epoch: 7. Loss: 2.3268723487854004. Accuracy: 10
Epoch: 8. Loss: 2.2902066707611084. Accuracy: 10
Epoch: 9. Loss: 2.305833101272583. Accuracy: 10
Epoch: 10. Loss: 2.31162428855896. Accuracy: 10
Epoch: 11. Loss: 2.292320489883423. Accuracy: 10
Epoch: 12. Loss: 2.3467929363250732. Accuracy: 10
Epoch: 13. Loss: 2.299393892288208. Accuracy: 10
Epoch: 14. Loss: 2.289851665496826. Accuracy: 10
[ 0.05399592392639796 64 tensor(10) ]
Loss: 2.289851665496826
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.004016724206339379

Epoch: 0. Loss: 0.1439436674118042. Accuracy: 81
Epoch: 1. Loss: 0.19913659989833832. Accuracy: 87
Epoch: 2. Loss: 0.19350938498973846. Accuracy: 88
Epoch: 3. Loss: 0.09624611586332321. Accuracy: 89
Epoch: 4. Loss: 0.03504392132163048. Accuracy: 90
Epoch: 5. Loss: 0.0793718695640564. Accuracy: 90
Epoch: 6. Loss: 0.037456098943948746. Accuracy: 91
Epoch: 7. Loss: 0.08371514081954956. Accuracy: 91
Epoch: 8. Loss: 0.2304658442735672. Accuracy: 90
Epoch: 9. Loss: 0.05121292546391487. Accuracy: 90
Epoch: 10. Loss: 0.052308905869722366. Accuracy: 91
Epoch: 11. Loss: 0.027850784361362457. Accuracy: 91
Epoch: 12. Loss: 0.06311320513486862. Accuracy: 91
Epoch: 13. Loss: 0.0247470885515213. Accuracy: 91
Epoch: 14. Loss: 0.06542401760816574. Accuracy: 91
[ 0.004016724206339379 256 tensor(91) ]
Loss: 0.06542401760816574
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0595653203183791

Epoch: 0. Loss: 2.3006515502929688. Accuracy: 10
Epoch: 1. Loss: 2.291811466217041. Accuracy: 10
Epoch: 2. Loss: 2.301443576812744. Accuracy: 10
Epoch: 3. Loss: 2.331404447555542. Accuracy: 10
Epoch: 4. Loss: 2.322885036468506. Accuracy: 10
Epoch: 5. Loss: 2.3151841163635254. Accuracy: 10
Epoch: 6. Loss: 2.300008535385132. Accuracy: 10
Epoch: 7. Loss: 2.3133959770202637. Accuracy: 10
Epoch: 8. Loss: 2.3246848583221436. Accuracy: 10
Epoch: 9. Loss: 2.284393548965454. Accuracy: 10
Epoch: 10. Loss: 2.297426462173462. Accuracy: 10
Epoch: 11. Loss: 2.307917833328247. Accuracy: 10
Epoch: 12. Loss: 2.3029110431671143. Accuracy: 10
Epoch: 13. Loss: 2.3124892711639404. Accuracy: 10
Epoch: 14. Loss: 2.315570592880249. Accuracy: 10
[ 0.0595653203183791 32 tensor(10) ]
Loss: 2.315570592880249
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.01249078865142103

Epoch: 0. Loss: 1.0257012844085693. Accuracy: 57
Epoch: 1. Loss: 0.9965383410453796. Accuracy: 62
Epoch: 2. Loss: 0.6558513641357422. Accuracy: 61
Epoch: 3. Loss: 0.572530210018158. Accuracy: 61
Epoch: 4. Loss: 0.809799313545227. Accuracy: 62
Epoch: 5. Loss: 0.391293466091156. Accuracy: 69
Epoch: 6. Loss: 0.5130985975265503. Accuracy: 68
Epoch: 7. Loss: 0.37041592597961426. Accuracy: 71
Epoch: 8. Loss: 0.9610368013381958. Accuracy: 70
Epoch: 9. Loss: 0.36051109433174133. Accuracy: 71
Epoch: 10. Loss: 0.3960711658000946. Accuracy: 72
Epoch: 11. Loss: 0.3975144028663635. Accuracy: 73
Epoch: 12. Loss: 0.24485290050506592. Accuracy: 74
Epoch: 13. Loss: 0.4214050769805908. Accuracy: 76
Epoch: 14. Loss: 0.12105556577444077. Accuracy: 75
[ 0.01249078865142103 32 tensor(75) ]
Loss: 0.12105556577444077
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.007252018621176794

Epoch: 0. Loss: 0.2646242380142212. Accuracy: 83
Epoch: 1. Loss: 0.21660564839839935. Accuracy: 83
Epoch: 2. Loss: 0.19134275615215302. Accuracy: 85
Epoch: 3. Loss: 0.1853008270263672. Accuracy: 84
Epoch: 4. Loss: 0.42030400037765503. Accuracy: 85
Epoch: 5. Loss: 0.11964024603366852. Accuracy: 86
Epoch: 6. Loss: 0.15897110104560852. Accuracy: 85
Epoch: 7. Loss: 0.2922024726867676. Accuracy: 86
Epoch: 8. Loss: 0.16864600777626038. Accuracy: 85
Epoch: 9. Loss: 0.08004923164844513. Accuracy: 85
Epoch: 10. Loss: 0.1974654346704483. Accuracy: 86
Epoch: 11. Loss: 0.08582179993391037. Accuracy: 84
Epoch: 12. Loss: 0.37218546867370605. Accuracy: 86
Epoch: 13. Loss: 0.27663668990135193. Accuracy: 86
Epoch: 14. Loss: 0.1651657074689865. Accuracy: 85
[ 0.007252018621176794 32 tensor(85) ]
Loss: 0.1651657074689865
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0901460324915806

Epoch: 0. Loss: 2.237802028656006. Accuracy: 10
Epoch: 1. Loss: 2.3117854595184326. Accuracy: 10
Epoch: 2. Loss: 2.3405861854553223. Accuracy: 10
Epoch: 3. Loss: 2.322774887084961. Accuracy: 10
Epoch: 4. Loss: 2.3079440593719482. Accuracy: 10
Epoch: 5. Loss: 2.3075695037841797. Accuracy: 10
Epoch: 6. Loss: 2.321781873703003. Accuracy: 10
Epoch: 7. Loss: 2.3553402423858643. Accuracy: 10
Epoch: 8. Loss: 2.299476385116577. Accuracy: 10
Epoch: 9. Loss: 2.300492763519287. Accuracy: 10
Epoch: 10. Loss: 2.2689783573150635. Accuracy: 10
Epoch: 11. Loss: 2.3159451484680176. Accuracy: 10
Epoch: 12. Loss: 2.304719924926758. Accuracy: 10
Epoch: 13. Loss: 2.303370952606201. Accuracy: 10
Epoch: 14. Loss: 2.319392204284668. Accuracy: 10
[ 0.0901460324915806 32 tensor(10) ]
Loss: 2.319392204284668
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.00026927991362221156

Epoch: 0. Loss: 0.4729755222797394. Accuracy: 75
Epoch: 1. Loss: 0.5787148475646973. Accuracy: 81
Epoch: 2. Loss: 0.27885812520980835. Accuracy: 82
Epoch: 3. Loss: 0.08829426020383835. Accuracy: 85
Epoch: 4. Loss: 0.5518372654914856. Accuracy: 85
Epoch: 5. Loss: 0.11379680782556534. Accuracy: 87
Epoch: 6. Loss: 0.15477439761161804. Accuracy: 87
Epoch: 7. Loss: 0.1636532098054886. Accuracy: 88
Epoch: 8. Loss: 0.17040395736694336. Accuracy: 88
Epoch: 9. Loss: 0.11751002818346024. Accuracy: 88
Epoch: 10. Loss: 0.36680904030799866. Accuracy: 88
Epoch: 11. Loss: 0.1250254064798355. Accuracy: 89
Epoch: 12. Loss: 0.05271133780479431. Accuracy: 89
Epoch: 13. Loss: 0.02779052034020424. Accuracy: 89
Epoch: 14. Loss: 0.04276863858103752. Accuracy: 90
[ 0.00026927991362221156 32 tensor(90) ]
Loss: 0.04276863858103752
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0006399989545548927

Epoch: 0. Loss: 0.3516983985900879. Accuracy: 82
Epoch: 1. Loss: 0.03699229657649994. Accuracy: 86
Epoch: 2. Loss: 0.11757922917604446. Accuracy: 88
Epoch: 3. Loss: 0.041539810597896576. Accuracy: 88
Epoch: 4. Loss: 0.180958554148674. Accuracy: 89
Epoch: 5. Loss: 0.02593366615474224. Accuracy: 89
Epoch: 6. Loss: 0.2999551296234131. Accuracy: 90
Epoch: 7. Loss: 0.05208943784236908. Accuracy: 91
Epoch: 8. Loss: 0.02457083761692047. Accuracy: 90
Epoch: 9. Loss: 0.11408855766057968. Accuracy: 90
Epoch: 10. Loss: 0.14820250868797302. Accuracy: 90
Epoch: 11. Loss: 0.006795123219490051. Accuracy: 91
Epoch: 12. Loss: 0.030302926898002625. Accuracy: 91
Epoch: 13. Loss: 0.0074064284563064575. Accuracy: 91
Epoch: 14. Loss: 0.1369936317205429. Accuracy: 91
[ 0.0006399989545548927 32 tensor(91) ]
Loss: 0.1369936317205429
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.05292275627149068

Epoch: 0. Loss: 0.6681333184242249. Accuracy: 68
Epoch: 1. Loss: 0.403428316116333. Accuracy: 69
Epoch: 2. Loss: 0.6015207171440125. Accuracy: 72
Epoch: 3. Loss: 0.4596487581729889. Accuracy: 73
Epoch: 4. Loss: 0.7852497100830078. Accuracy: 73
Epoch: 5. Loss: 0.6479368805885315. Accuracy: 73
Epoch: 6. Loss: 0.5675410032272339. Accuracy: 73
Epoch: 7. Loss: 0.6693251729011536. Accuracy: 73
Epoch: 8. Loss: 0.45856234431266785. Accuracy: 73
Epoch: 9. Loss: 0.4815025329589844. Accuracy: 73
Epoch: 10. Loss: 0.4532327950000763. Accuracy: 72
Epoch: 11. Loss: 0.34747710824012756. Accuracy: 74
Epoch: 12. Loss: 0.5457519888877869. Accuracy: 69
Epoch: 13. Loss: 0.37817585468292236. Accuracy: 72
Epoch: 14. Loss: 0.5001822710037231. Accuracy: 72
[ 0.05292275627149068 256 tensor(72) ]
Loss: 0.5001822710037231
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.006519568161032333

Epoch: 0. Loss: 0.12198789417743683. Accuracy: 87
Epoch: 1. Loss: 0.08482564240694046. Accuracy: 88
Epoch: 2. Loss: 0.27882617712020874. Accuracy: 89
Epoch: 3. Loss: 0.052988529205322266. Accuracy: 88
Epoch: 4. Loss: 0.1361100971698761. Accuracy: 89
Epoch: 5. Loss: 0.027524329721927643. Accuracy: 89
Epoch: 6. Loss: 0.0026281774044036865. Accuracy: 88
Epoch: 7. Loss: 0.29757386445999146. Accuracy: 89
Epoch: 8. Loss: 0.31648895144462585. Accuracy: 89
Epoch: 9. Loss: 0.022546842694282532. Accuracy: 89
Epoch: 10. Loss: 0.15508338809013367. Accuracy: 88
Epoch: 11. Loss: 0.17319902777671814. Accuracy: 89
Epoch: 12. Loss: 0.07059643417596817. Accuracy: 89
Epoch: 13. Loss: 0.5140106678009033. Accuracy: 88
Epoch: 14. Loss: 0.11418931186199188. Accuracy: 88
[ 0.006519568161032333 32 tensor(88) ]
Loss: 0.11418931186199188
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.03312448123923109

Epoch: 0. Loss: 0.6745322346687317. Accuracy: 66
Epoch: 1. Loss: 0.5274993777275085. Accuracy: 67
Epoch: 2. Loss: 0.590351939201355. Accuracy: 67
Epoch: 3. Loss: 0.7938955426216125. Accuracy: 68
Epoch: 4. Loss: 0.47050273418426514. Accuracy: 70
Epoch: 5. Loss: 0.6008983254432678. Accuracy: 70
Epoch: 6. Loss: 0.5332024693489075. Accuracy: 70
Epoch: 7. Loss: 0.5884518027305603. Accuracy: 70
Epoch: 8. Loss: 0.7209959626197815. Accuracy: 67
Epoch: 9. Loss: 0.6090255379676819. Accuracy: 68
Epoch: 10. Loss: 0.5404564738273621. Accuracy: 72
Epoch: 11. Loss: 0.3419172763824463. Accuracy: 73
Epoch: 12. Loss: 0.419354647397995. Accuracy: 75
Epoch: 13. Loss: 0.48512697219848633. Accuracy: 76
Epoch: 14. Loss: 0.46510493755340576. Accuracy: 75
[ 0.03312448123923109 128 tensor(75) ]
Loss: 0.46510493755340576
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.025483701790689657

Epoch: 0. Loss: 0.7903494834899902. Accuracy: 66
Epoch: 1. Loss: 0.63103848695755. Accuracy: 66
Epoch: 2. Loss: 0.5347244739532471. Accuracy: 67
Epoch: 3. Loss: 0.6415963768959045. Accuracy: 67
Epoch: 4. Loss: 0.597960889339447. Accuracy: 69
Epoch: 5. Loss: 0.718569278717041. Accuracy: 67
Epoch: 6. Loss: 0.6290026307106018. Accuracy: 69
Epoch: 7. Loss: 0.6127490401268005. Accuracy: 70
Epoch: 8. Loss: 0.5535406470298767. Accuracy: 71
Epoch: 9. Loss: 0.6129029393196106. Accuracy: 70
Epoch: 10. Loss: 0.46822452545166016. Accuracy: 70
Epoch: 11. Loss: 0.703826904296875. Accuracy: 70
Epoch: 12. Loss: 0.8595387935638428. Accuracy: 69
Epoch: 13. Loss: 0.47542905807495117. Accuracy: 70
Epoch: 14. Loss: 0.54140704870224. Accuracy: 71
[ 0.025483701790689657 128 tensor(71) ]
Loss: 0.54140704870224
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.06437857986468642

Epoch: 0. Loss: 2.300740957260132. Accuracy: 10
Epoch: 1. Loss: 2.3110854625701904. Accuracy: 10
Epoch: 2. Loss: 2.308922290802002. Accuracy: 10
Epoch: 3. Loss: 2.3015432357788086. Accuracy: 10
Epoch: 4. Loss: 2.3080637454986572. Accuracy: 10
Epoch: 5. Loss: 2.315135955810547. Accuracy: 10
Epoch: 6. Loss: 2.308823347091675. Accuracy: 10
Epoch: 7. Loss: 2.316995859146118. Accuracy: 10
Epoch: 8. Loss: 2.299194574356079. Accuracy: 10
Epoch: 9. Loss: 2.299462080001831. Accuracy: 10
Epoch: 10. Loss: 2.3112850189208984. Accuracy: 10
Epoch: 11. Loss: 2.3110344409942627. Accuracy: 10
Epoch: 12. Loss: 2.2993438243865967. Accuracy: 10
Epoch: 13. Loss: 2.3124282360076904. Accuracy: 10
Epoch: 14. Loss: 2.293653726577759. Accuracy: 10
[ 0.06437857986468642 128 tensor(10) ]
Loss: 2.293653726577759
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.005352591471846662

Epoch: 0. Loss: 0.4036538600921631. Accuracy: 87
Epoch: 1. Loss: 0.17049948871135712. Accuracy: 89
Epoch: 2. Loss: 0.14360707998275757. Accuracy: 90
Epoch: 3. Loss: 0.0362761989235878. Accuracy: 90
Epoch: 4. Loss: 0.015646353363990784. Accuracy: 91
Epoch: 5. Loss: 0.31731534004211426. Accuracy: 91
Epoch: 6. Loss: 0.002679109573364258. Accuracy: 91
Epoch: 7. Loss: 0.08587177097797394. Accuracy: 91
Epoch: 8. Loss: 0.06665270030498505. Accuracy: 90
Epoch: 9. Loss: 0.04672113060951233. Accuracy: 92
Epoch: 10. Loss: 0.003741830587387085. Accuracy: 91
Epoch: 11. Loss: 0.06554169952869415. Accuracy: 91
Epoch: 12. Loss: 0.16825321316719055. Accuracy: 91
Epoch: 13. Loss: 0.051664963364601135. Accuracy: 92
Epoch: 14. Loss: 0.02448911964893341. Accuracy: 91
[ 0.005352591471846662 64 tensor(91) ]
Loss: 0.02448911964893341
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0012304907694337564

Epoch: 0. Loss: 0.09906665235757828. Accuracy: 84
Epoch: 1. Loss: 0.20550014078617096. Accuracy: 89
Epoch: 2. Loss: 0.18822771310806274. Accuracy: 90
Epoch: 3. Loss: 0.08377555012702942. Accuracy: 90
Epoch: 4. Loss: 0.098909892141819. Accuracy: 90
Epoch: 5. Loss: 0.04038283973932266. Accuracy: 91
Epoch: 6. Loss: 0.019616015255451202. Accuracy: 91
Epoch: 7. Loss: 0.003573507070541382. Accuracy: 92
Epoch: 8. Loss: 0.04572143405675888. Accuracy: 91
Epoch: 9. Loss: 0.002991423010826111. Accuracy: 92
Epoch: 10. Loss: 0.021510165184736252. Accuracy: 91
Epoch: 11. Loss: 0.00656437873840332. Accuracy: 91
Epoch: 12. Loss: 0.0791495069861412. Accuracy: 92
Epoch: 13. Loss: 0.012435071170330048. Accuracy: 91
Epoch: 14. Loss: 0.06860382854938507. Accuracy: 92
[ 0.0012304907694337564 32 tensor(92) ]
Loss: 0.06860382854938507
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.07761612160332262

Epoch: 0. Loss: 2.318655014038086. Accuracy: 10
Epoch: 1. Loss: 2.293076992034912. Accuracy: 10
Epoch: 2. Loss: 2.302042007446289. Accuracy: 10
Epoch: 3. Loss: 2.30422043800354. Accuracy: 10
Epoch: 4. Loss: 2.3403027057647705. Accuracy: 10
Epoch: 5. Loss: 2.3005566596984863. Accuracy: 10
Epoch: 6. Loss: 2.24214768409729. Accuracy: 10
Epoch: 7. Loss: 2.2997026443481445. Accuracy: 10
Epoch: 8. Loss: 2.3116517066955566. Accuracy: 10
Epoch: 9. Loss: 2.25495982170105. Accuracy: 10
Epoch: 10. Loss: 2.300778865814209. Accuracy: 10
Epoch: 11. Loss: 2.3123466968536377. Accuracy: 10
Epoch: 12. Loss: 2.3042140007019043. Accuracy: 10
Epoch: 13. Loss: 3.001147508621216. Accuracy: 10
Epoch: 14. Loss: 2.285158634185791. Accuracy: 10
[ 0.07761612160332262 32 tensor(10) ]
Loss: 2.285158634185791
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.09180379960702956

Epoch: 0. Loss: 2.3202126026153564. Accuracy: 10
Epoch: 1. Loss: 2.314739465713501. Accuracy: 10
Epoch: 2. Loss: 2.3157577514648438. Accuracy: 10
Epoch: 3. Loss: 2.3089444637298584. Accuracy: 10
Epoch: 4. Loss: 2.3075883388519287. Accuracy: 10
Epoch: 5. Loss: 2.3039321899414062. Accuracy: 10
Epoch: 6. Loss: 2.3050286769866943. Accuracy: 10
Epoch: 7. Loss: 2.317958116531372. Accuracy: 10
Epoch: 8. Loss: 2.3311643600463867. Accuracy: 10
Epoch: 9. Loss: 2.2953293323516846. Accuracy: 10
Epoch: 10. Loss: 2.300398826599121. Accuracy: 10
Epoch: 11. Loss: 2.324761152267456. Accuracy: 10
Epoch: 12. Loss: 2.309558629989624. Accuracy: 10
Epoch: 13. Loss: 2.310225248336792. Accuracy: 10
Epoch: 14. Loss: 2.309603452682495. Accuracy: 10
[ 0.09180379960702956 128 tensor(10) ]
Loss: 2.309603452682495
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.005575358031078386

Epoch: 0. Loss: 0.03595414757728577. Accuracy: 88
Epoch: 1. Loss: 0.09293816983699799. Accuracy: 90
Epoch: 2. Loss: 0.009287968277931213. Accuracy: 91
Epoch: 3. Loss: 0.38146719336509705. Accuracy: 90
Epoch: 4. Loss: 0.036576732993125916. Accuracy: 92
Epoch: 5. Loss: 0.007768735289573669. Accuracy: 91
Epoch: 6. Loss: 0.007760912179946899. Accuracy: 91
Epoch: 7. Loss: 0.0212201327085495. Accuracy: 90
Epoch: 8. Loss: 0.14684446156024933. Accuracy: 91
Epoch: 9. Loss: 0.014692291617393494. Accuracy: 91
Epoch: 10. Loss: 0.0015642493963241577. Accuracy: 91
Epoch: 11. Loss: 0.0194331556558609. Accuracy: 91
Epoch: 12. Loss: 0.009979143738746643. Accuracy: 92
Epoch: 13. Loss: 0.012362286448478699. Accuracy: 92
Epoch: 14. Loss: 0.006152093410491943. Accuracy: 91
[ 0.005575358031078386 64 tensor(91) ]
Loss: 0.006152093410491943
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.0551794151377897

Epoch: 0. Loss: 1.1574331521987915. Accuracy: 61
Epoch: 1. Loss: 0.6942296624183655. Accuracy: 64
Epoch: 2. Loss: 0.4916793406009674. Accuracy: 68
Epoch: 3. Loss: 0.6482585072517395. Accuracy: 67
Epoch: 4. Loss: 0.7470662593841553. Accuracy: 67
Epoch: 5. Loss: 0.6786055564880371. Accuracy: 69
Epoch: 6. Loss: 0.5007635951042175. Accuracy: 70
Epoch: 7. Loss: 0.42754730582237244. Accuracy: 68
Epoch: 8. Loss: 0.37341439723968506. Accuracy: 70
Epoch: 9. Loss: 0.6802563071250916. Accuracy: 69
Epoch: 10. Loss: 0.4808441698551178. Accuracy: 68
Epoch: 11. Loss: 0.6115880012512207. Accuracy: 69
Epoch: 12. Loss: 0.5388747453689575. Accuracy: 69
Epoch: 13. Loss: 0.7625765204429626. Accuracy: 67
Epoch: 14. Loss: 0.4534189701080322. Accuracy: 69
[ 0.0551794151377897 256 tensor(69) ]
Loss: 0.4534189701080322
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0013134558497964906

Epoch: 0. Loss: 0.10065066069364548. Accuracy: 84
Epoch: 1. Loss: 0.38081660866737366. Accuracy: 88
Epoch: 2. Loss: 0.06455560028553009. Accuracy: 89
Epoch: 3. Loss: 0.12646424770355225. Accuracy: 90
Epoch: 4. Loss: 0.1653231829404831. Accuracy: 89
Epoch: 5. Loss: 0.013755515217781067. Accuracy: 90
Epoch: 6. Loss: 0.0679999366402626. Accuracy: 91
Epoch: 7. Loss: 0.03739243745803833. Accuracy: 91
Epoch: 8. Loss: 0.04413673281669617. Accuracy: 90
Epoch: 9. Loss: 0.0400257334113121. Accuracy: 91
Epoch: 10. Loss: 0.033841706812381744. Accuracy: 91
Epoch: 11. Loss: 0.06472724676132202. Accuracy: 91
Epoch: 12. Loss: 0.03613372892141342. Accuracy: 92
Epoch: 13. Loss: 0.015206709504127502. Accuracy: 92
Epoch: 14. Loss: 0.08036841452121735. Accuracy: 91
[ 0.0013134558497964906 32 tensor(91) ]
Loss: 0.08036841452121735
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.02677590023293823

Epoch: 0. Loss: 0.7377750873565674. Accuracy: 74
Epoch: 1. Loss: 0.28529709577560425. Accuracy: 76
Epoch: 2. Loss: 0.28648942708969116. Accuracy: 77
Epoch: 3. Loss: 0.45599499344825745. Accuracy: 76
Epoch: 4. Loss: 0.2224411517381668. Accuracy: 76
Epoch: 5. Loss: 0.49287450313568115. Accuracy: 77
Epoch: 6. Loss: 0.6172341108322144. Accuracy: 76
Epoch: 7. Loss: 0.2787729501724243. Accuracy: 76
Epoch: 8. Loss: 0.28085917234420776. Accuracy: 77
Epoch: 9. Loss: 0.35003724694252014. Accuracy: 77
Epoch: 10. Loss: 0.39348894357681274. Accuracy: 77
Epoch: 11. Loss: 0.10168390721082687. Accuracy: 75
Epoch: 12. Loss: 0.28398242592811584. Accuracy: 78
Epoch: 13. Loss: 0.2899617552757263. Accuracy: 75
Epoch: 14. Loss: 0.33208030462265015. Accuracy: 78
[ 0.02677590023293823 32 tensor(78) ]
Loss: 0.33208030462265015
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.013484233419707005

Epoch: 0. Loss: 0.0814112052321434. Accuracy: 80
Epoch: 1. Loss: 0.2060590237379074. Accuracy: 81
Epoch: 2. Loss: 0.1367306262254715. Accuracy: 83
Epoch: 3. Loss: 0.18230445683002472. Accuracy: 83
Epoch: 4. Loss: 0.02613098919391632. Accuracy: 83
Epoch: 5. Loss: 0.12341524660587311. Accuracy: 85
Epoch: 6. Loss: 0.3504214584827423. Accuracy: 82
Epoch: 7. Loss: 0.27067211270332336. Accuracy: 84
Epoch: 8. Loss: 0.5628945231437683. Accuracy: 86
Epoch: 9. Loss: 0.09434764087200165. Accuracy: 84
Epoch: 10. Loss: 0.19402575492858887. Accuracy: 85
Epoch: 11. Loss: 0.1742067039012909. Accuracy: 85
Epoch: 12. Loss: 0.13289783895015717. Accuracy: 85
Epoch: 13. Loss: 0.3492017686367035. Accuracy: 85
Epoch: 14. Loss: 0.04335886240005493. Accuracy: 85
[ 0.013484233419707005 64 tensor(85) ]
Loss: 0.04335886240005493
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.059229899250182905

Epoch: 0. Loss: 0.6868431568145752. Accuracy: 59
Epoch: 1. Loss: 0.6252541542053223. Accuracy: 62
Epoch: 2. Loss: 0.7024080753326416. Accuracy: 65
Epoch: 3. Loss: 0.5780668258666992. Accuracy: 66
Epoch: 4. Loss: 0.7559718489646912. Accuracy: 65
Epoch: 5. Loss: 0.5361007452011108. Accuracy: 63
Epoch: 6. Loss: 0.5372044444084167. Accuracy: 66
Epoch: 7. Loss: 0.8234936594963074. Accuracy: 65
Epoch: 8. Loss: 0.49878570437431335. Accuracy: 66
Epoch: 9. Loss: 0.5229836702346802. Accuracy: 65
Epoch: 10. Loss: 0.7881141304969788. Accuracy: 66
Epoch: 11. Loss: 0.7667381167411804. Accuracy: 65
Epoch: 12. Loss: 0.5628225803375244. Accuracy: 65
Epoch: 13. Loss: 0.5790405869483948. Accuracy: 66
Epoch: 14. Loss: 1.312286615371704. Accuracy: 66
[ 0.059229899250182905 256 tensor(66) ]
Loss: 1.312286615371704
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.00527758595089884

Epoch: 0. Loss: 0.30735889077186584. Accuracy: 85
Epoch: 1. Loss: 0.09201505780220032. Accuracy: 87
Epoch: 2. Loss: 0.08829410374164581. Accuracy: 89
Epoch: 3. Loss: 0.033371664583683014. Accuracy: 89
Epoch: 4. Loss: 0.02600918710231781. Accuracy: 89
Epoch: 5. Loss: 0.2140263170003891. Accuracy: 90
Epoch: 6. Loss: 0.011704392731189728. Accuracy: 91
Epoch: 7. Loss: 0.003916487097740173. Accuracy: 91
Epoch: 8. Loss: 0.04923608899116516. Accuracy: 91
Epoch: 9. Loss: 0.08188799023628235. Accuracy: 91
Epoch: 10. Loss: 0.09313971549272537. Accuracy: 90
Epoch: 11. Loss: 0.2763097584247589. Accuracy: 90
Epoch: 12. Loss: 0.31962957978248596. Accuracy: 91
Epoch: 13. Loss: 0.06547698378562927. Accuracy: 91
Epoch: 14. Loss: 0.16495412588119507. Accuracy: 91
[ 0.00527758595089884 64 tensor(91) ]
Loss: 0.16495412588119507
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.015066349945505757

Epoch: 0. Loss: 0.23726099729537964. Accuracy: 72
Epoch: 1. Loss: 0.21422502398490906. Accuracy: 76
Epoch: 2. Loss: 0.762387752532959. Accuracy: 76
Epoch: 3. Loss: 0.16453498601913452. Accuracy: 77
Epoch: 4. Loss: 0.4968753159046173. Accuracy: 75
Epoch: 5. Loss: 0.33626502752304077. Accuracy: 76
Epoch: 6. Loss: 0.8172965049743652. Accuracy: 76
Epoch: 7. Loss: 0.4283801019191742. Accuracy: 75
Epoch: 8. Loss: 0.06974025815725327. Accuracy: 75
Epoch: 9. Loss: 0.2624503970146179. Accuracy: 77
Epoch: 10. Loss: 0.6336143016815186. Accuracy: 74
Epoch: 11. Loss: 0.22189992666244507. Accuracy: 75
Epoch: 12. Loss: 0.4367007315158844. Accuracy: 76
Epoch: 13. Loss: 0.20522254705429077. Accuracy: 76
Epoch: 14. Loss: 0.4631827473640442. Accuracy: 75
[ 0.015066349945505757 64 tensor(75) ]
Loss: 0.4631827473640442
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.05902340129422236

Epoch: 0. Loss: 2.3093228340148926. Accuracy: 10
Epoch: 1. Loss: 2.308199644088745. Accuracy: 10
Epoch: 2. Loss: 2.3334479331970215. Accuracy: 10
Epoch: 3. Loss: 2.303133249282837. Accuracy: 10
Epoch: 4. Loss: 2.3213438987731934. Accuracy: 10
Epoch: 5. Loss: 2.3021886348724365. Accuracy: 10
Epoch: 6. Loss: 2.3135318756103516. Accuracy: 10
Epoch: 7. Loss: 2.3123347759246826. Accuracy: 10
Epoch: 8. Loss: 2.3096487522125244. Accuracy: 10
Epoch: 9. Loss: 2.291977643966675. Accuracy: 10
Epoch: 10. Loss: 2.3038082122802734. Accuracy: 10
Epoch: 11. Loss: 2.3177857398986816. Accuracy: 10
Epoch: 12. Loss: 2.307378053665161. Accuracy: 10
Epoch: 13. Loss: 2.299651622772217. Accuracy: 10
Epoch: 14. Loss: 2.30438232421875. Accuracy: 10
[ 0.05902340129422236 256 tensor(10) ]
Loss: 2.30438232421875
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0009869869027387902

Epoch: 0. Loss: 0.5747859477996826. Accuracy: 84
Epoch: 1. Loss: 0.07512641698122025. Accuracy: 88
Epoch: 2. Loss: 0.3377179801464081. Accuracy: 89
Epoch: 3. Loss: 0.1457957923412323. Accuracy: 89
Epoch: 4. Loss: 0.08933266997337341. Accuracy: 90
Epoch: 5. Loss: 0.10669346153736115. Accuracy: 91
Epoch: 6. Loss: 0.012216895818710327. Accuracy: 91
Epoch: 7. Loss: 0.1918638050556183. Accuracy: 92
Epoch: 8. Loss: 0.0054624080657958984. Accuracy: 91
Epoch: 9. Loss: 0.0898917019367218. Accuracy: 91
Epoch: 10. Loss: 0.024883057922124863. Accuracy: 91
Epoch: 11. Loss: 0.024296831339597702. Accuracy: 92
Epoch: 12. Loss: 0.080018050968647. Accuracy: 91
Epoch: 13. Loss: 0.020758338272571564. Accuracy: 92
Epoch: 14. Loss: 0.06955307722091675. Accuracy: 92
[ 0.0009869869027387902 32 tensor(92) ]
Loss: 0.06955307722091675
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.07517439202526939

Epoch: 0. Loss: 1.003682255744934. Accuracy: 51
Epoch: 1. Loss: 0.8815988898277283. Accuracy: 53
Epoch: 2. Loss: 0.7427093386650085. Accuracy: 53
Epoch: 3. Loss: 1.177939534187317. Accuracy: 55
Epoch: 4. Loss: 1.0701528787612915. Accuracy: 49
Epoch: 5. Loss: 1.0465196371078491. Accuracy: 55
Epoch: 6. Loss: 0.9554460048675537. Accuracy: 55
Epoch: 7. Loss: 0.8152024149894714. Accuracy: 55
Epoch: 8. Loss: 0.8657898306846619. Accuracy: 55
Epoch: 9. Loss: 0.8548287749290466. Accuracy: 54
Epoch: 10. Loss: 1.3786282539367676. Accuracy: 55
Epoch: 11. Loss: 0.8039994835853577. Accuracy: 54
Epoch: 12. Loss: 1.0798909664154053. Accuracy: 53
Epoch: 13. Loss: 0.7932516932487488. Accuracy: 54
Epoch: 14. Loss: 0.7841446399688721. Accuracy: 53
[ 0.07517439202526939 128 tensor(53) ]
Loss: 0.7841446399688721
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.013759474049652805

Epoch: 0. Loss: 0.10631052404642105. Accuracy: 81
Epoch: 1. Loss: 0.09872408956289291. Accuracy: 85
Epoch: 2. Loss: 0.14064913988113403. Accuracy: 84
Epoch: 3. Loss: 0.3295740485191345. Accuracy: 86
Epoch: 4. Loss: 0.061013296246528625. Accuracy: 84
Epoch: 5. Loss: 0.1789020448923111. Accuracy: 85
Epoch: 6. Loss: 0.1334054172039032. Accuracy: 86
Epoch: 7. Loss: 0.11352149397134781. Accuracy: 86
Epoch: 8. Loss: 0.22060328722000122. Accuracy: 84
Epoch: 9. Loss: 0.12919580936431885. Accuracy: 85
Epoch: 10. Loss: 0.40258222818374634. Accuracy: 85
Epoch: 11. Loss: 0.12961885333061218. Accuracy: 86
Epoch: 12. Loss: 0.1667824536561966. Accuracy: 85
Epoch: 13. Loss: 0.5168472528457642. Accuracy: 85
Epoch: 14. Loss: 0.14682188630104065. Accuracy: 86
[ 0.013759474049652805 64 tensor(86) ]
Loss: 0.14682188630104065
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.013969936524384862

Epoch: 0. Loss: 0.21344710886478424. Accuracy: 85
Epoch: 1. Loss: 0.13212133944034576. Accuracy: 86
Epoch: 2. Loss: 0.3185092806816101. Accuracy: 87
Epoch: 3. Loss: 0.23228488862514496. Accuracy: 87
Epoch: 4. Loss: 0.14560824632644653. Accuracy: 87
Epoch: 5. Loss: 0.1309126317501068. Accuracy: 87
Epoch: 6. Loss: 0.12253327667713165. Accuracy: 87
Epoch: 7. Loss: 0.23398712277412415. Accuracy: 87
Epoch: 8. Loss: 0.2812618017196655. Accuracy: 88
Epoch: 9. Loss: 0.11482859402894974. Accuracy: 88
Epoch: 10. Loss: 0.10786663740873337. Accuracy: 87
Epoch: 11. Loss: 0.16239354014396667. Accuracy: 88
Epoch: 12. Loss: 0.03124658763408661. Accuracy: 88
Epoch: 13. Loss: 0.13494369387626648. Accuracy: 87
Epoch: 14. Loss: 0.10073017328977585. Accuracy: 89
[ 0.013969936524384862 64 tensor(89) ]
Loss: 0.10073017328977585
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0014349121575859105

Epoch: 0. Loss: 0.0635938048362732. Accuracy: 84
Epoch: 1. Loss: 0.28370553255081177. Accuracy: 89
Epoch: 2. Loss: 0.12018010765314102. Accuracy: 89
Epoch: 3. Loss: 0.29481253027915955. Accuracy: 90
Epoch: 4. Loss: 0.15074679255485535. Accuracy: 90
Epoch: 5. Loss: 0.06685829162597656. Accuracy: 91
Epoch: 6. Loss: 0.17587444186210632. Accuracy: 91
Epoch: 7. Loss: 0.09734134376049042. Accuracy: 91
Epoch: 8. Loss: 0.1413256675004959. Accuracy: 91
Epoch: 9. Loss: 0.013568684458732605. Accuracy: 92
Epoch: 10. Loss: 0.17964774370193481. Accuracy: 92
Epoch: 11. Loss: 0.04047567397356033. Accuracy: 92
Epoch: 12. Loss: 0.03335059434175491. Accuracy: 92
Epoch: 13. Loss: 0.002592235803604126. Accuracy: 92
Epoch: 14. Loss: 0.060869451612234116. Accuracy: 92
[ 0.0014349121575859105 32 tensor(92) ]
Loss: 0.060869451612234116
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.0020686534549506407

Epoch: 0. Loss: 0.3620738685131073. Accuracy: 79
Epoch: 1. Loss: 0.21986663341522217. Accuracy: 84
Epoch: 2. Loss: 0.18000324070453644. Accuracy: 87
Epoch: 3. Loss: 0.06945072114467621. Accuracy: 87
Epoch: 4. Loss: 0.12643994390964508. Accuracy: 89
Epoch: 5. Loss: 0.10740635544061661. Accuracy: 89
Epoch: 6. Loss: 0.04820697009563446. Accuracy: 90
Epoch: 7. Loss: 0.09231098741292953. Accuracy: 90
Epoch: 8. Loss: 0.13722342252731323. Accuracy: 90
Epoch: 9. Loss: 0.04240766540169716. Accuracy: 90
Epoch: 10. Loss: 0.08195270597934723. Accuracy: 91
Epoch: 11. Loss: 0.025126582011580467. Accuracy: 91
Epoch: 12. Loss: 0.14462684094905853. Accuracy: 90
Epoch: 13. Loss: 0.07136336714029312. Accuracy: 91
Epoch: 14. Loss: 0.022733228281140327. Accuracy: 91
[ 0.0020686534549506407 256 tensor(91) ]
Loss: 0.022733228281140327
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.017751324573501114

Epoch: 0. Loss: 0.2798449397087097. Accuracy: 75
Epoch: 1. Loss: 0.38966402411460876. Accuracy: 79
Epoch: 2. Loss: 0.514864981174469. Accuracy: 79
Epoch: 3. Loss: 0.40667250752449036. Accuracy: 80
Epoch: 4. Loss: 0.21585816144943237. Accuracy: 80
Epoch: 5. Loss: 0.4509528577327728. Accuracy: 83
Epoch: 6. Loss: 0.22865164279937744. Accuracy: 81
Epoch: 7. Loss: 0.3081635534763336. Accuracy: 81
Epoch: 8. Loss: 0.2717483937740326. Accuracy: 81
Epoch: 9. Loss: 0.390605092048645. Accuracy: 81
Epoch: 10. Loss: 0.29262757301330566. Accuracy: 80
Epoch: 11. Loss: 0.27818095684051514. Accuracy: 81
Epoch: 12. Loss: 0.24049921333789825. Accuracy: 82
Epoch: 13. Loss: 0.46981796622276306. Accuracy: 82
Epoch: 14. Loss: 0.15480466187000275. Accuracy: 81
[ 0.017751324573501114 256 tensor(81) ]
Loss: 0.15480466187000275
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.011714160796047628

Epoch: 0. Loss: 0.19350117444992065. Accuracy: 78
Epoch: 1. Loss: 0.40468230843544006. Accuracy: 80
Epoch: 2. Loss: 0.14825598895549774. Accuracy: 79
Epoch: 3. Loss: 0.21810778975486755. Accuracy: 79
Epoch: 4. Loss: 0.3468366265296936. Accuracy: 81
Epoch: 5. Loss: 0.2169584035873413. Accuracy: 82
Epoch: 6. Loss: 0.5493682622909546. Accuracy: 83
Epoch: 7. Loss: 0.07445508241653442. Accuracy: 82
Epoch: 8. Loss: 0.23374956846237183. Accuracy: 83
Epoch: 9. Loss: 0.685820460319519. Accuracy: 82
Epoch: 10. Loss: 0.43096357583999634. Accuracy: 84
Epoch: 11. Loss: 0.24085836112499237. Accuracy: 82
Epoch: 12. Loss: 0.14651140570640564. Accuracy: 82
Epoch: 13. Loss: 0.1899186223745346. Accuracy: 83
Epoch: 14. Loss: 0.239114448428154. Accuracy: 81
[ 0.011714160796047628 32 tensor(81) ]
Loss: 0.239114448428154
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.09578290379104841

Epoch: 0. Loss: 2.292792558670044. Accuracy: 10
Epoch: 1. Loss: 2.2983644008636475. Accuracy: 10
Epoch: 2. Loss: 2.302140474319458. Accuracy: 10
Epoch: 3. Loss: 2.297492265701294. Accuracy: 10
Epoch: 4. Loss: 2.306259870529175. Accuracy: 10
Epoch: 5. Loss: 2.3018453121185303. Accuracy: 10
Epoch: 6. Loss: 2.2897040843963623. Accuracy: 10
Epoch: 7. Loss: 2.305008888244629. Accuracy: 10
Epoch: 8. Loss: 2.3173112869262695. Accuracy: 10
Epoch: 9. Loss: 2.3041605949401855. Accuracy: 10
Epoch: 10. Loss: 2.3078536987304688. Accuracy: 10
Epoch: 11. Loss: 2.2927260398864746. Accuracy: 10
Epoch: 12. Loss: 2.3222439289093018. Accuracy: 10
Epoch: 13. Loss: 2.2978413105010986. Accuracy: 10
Epoch: 14. Loss: 2.3056881427764893. Accuracy: 10
[ 0.09578290379104841 128 tensor(10) ]
Loss: 2.3056881427764893
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.08955212923783407

Epoch: 0. Loss: 2.289825677871704. Accuracy: 10
Epoch: 1. Loss: 2.2996599674224854. Accuracy: 10
Epoch: 2. Loss: 2.305788040161133. Accuracy: 10
Epoch: 3. Loss: 2.2987935543060303. Accuracy: 10
Epoch: 4. Loss: 2.310577630996704. Accuracy: 10
Epoch: 5. Loss: 2.3084731101989746. Accuracy: 10
Epoch: 6. Loss: 2.3106603622436523. Accuracy: 10
Epoch: 7. Loss: 2.3004887104034424. Accuracy: 10
Epoch: 8. Loss: 2.314990282058716. Accuracy: 10
Epoch: 9. Loss: 2.319998025894165. Accuracy: 10
Epoch: 10. Loss: 2.3177497386932373. Accuracy: 10
Epoch: 11. Loss: 2.3257665634155273. Accuracy: 10
Epoch: 12. Loss: 2.298814058303833. Accuracy: 10
Epoch: 13. Loss: 2.3016247749328613. Accuracy: 10
Epoch: 14. Loss: 2.313286066055298. Accuracy: 10
[ 0.08955212923783407 256 tensor(10) ]
Loss: 2.313286066055298
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.0017511353480725517

Epoch: 0. Loss: 0.42790687084198. Accuracy: 75
Epoch: 1. Loss: 0.28726035356521606. Accuracy: 82
Epoch: 2. Loss: 0.19192831218242645. Accuracy: 86
Epoch: 3. Loss: 0.24707917869091034. Accuracy: 87
Epoch: 4. Loss: 0.17895416915416718. Accuracy: 88
Epoch: 5. Loss: 0.1636463701725006. Accuracy: 88
Epoch: 6. Loss: 0.1290518343448639. Accuracy: 89
Epoch: 7. Loss: 0.06110478937625885. Accuracy: 89
Epoch: 8. Loss: 0.07516395300626755. Accuracy: 90
Epoch: 9. Loss: 0.17472733557224274. Accuracy: 90
Epoch: 10. Loss: 0.10459663718938828. Accuracy: 90
Epoch: 11. Loss: 0.08306201547384262. Accuracy: 90
Epoch: 12. Loss: 0.02128599025309086. Accuracy: 90
Epoch: 13. Loss: 0.0414307564496994. Accuracy: 90
Epoch: 14. Loss: 0.09873690456151962. Accuracy: 91
[ 0.0017511353480725517 256 tensor(91) ]
Loss: 0.09873690456151962
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.002492108130628435

Epoch: 0. Loss: 0.18357141315937042. Accuracy: 79
Epoch: 1. Loss: 0.15479178726673126. Accuracy: 85
Epoch: 2. Loss: 0.1713128536939621. Accuracy: 87
Epoch: 3. Loss: 0.14396636188030243. Accuracy: 88
Epoch: 4. Loss: 0.14467935264110565. Accuracy: 89
Epoch: 5. Loss: 0.24240626394748688. Accuracy: 89
Epoch: 6. Loss: 0.08858034759759903. Accuracy: 89
Epoch: 7. Loss: 0.20563693344593048. Accuracy: 90
Epoch: 8. Loss: 0.17667454481124878. Accuracy: 90
Epoch: 9. Loss: 0.06278187036514282. Accuracy: 90
Epoch: 10. Loss: 0.10674861818552017. Accuracy: 91
Epoch: 11. Loss: 0.12545108795166016. Accuracy: 90
Epoch: 12. Loss: 0.11121080070734024. Accuracy: 90
Epoch: 13. Loss: 0.06708540767431259. Accuracy: 90
Epoch: 14. Loss: 0.24443359673023224. Accuracy: 90
[ 0.002492108130628435 256 tensor(90) ]
Loss: 0.24443359673023224
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.09924230018397677

Epoch: 0. Loss: 2.3020756244659424. Accuracy: 10
Epoch: 1. Loss: 2.3032479286193848. Accuracy: 10
Epoch: 2. Loss: 2.2973735332489014. Accuracy: 10
Epoch: 3. Loss: 2.3124847412109375. Accuracy: 10
Epoch: 4. Loss: 2.307006597518921. Accuracy: 10
Epoch: 5. Loss: 2.312117576599121. Accuracy: 10
Epoch: 6. Loss: 2.2985761165618896. Accuracy: 10
Epoch: 7. Loss: 2.305664300918579. Accuracy: 10
Epoch: 8. Loss: 2.31062650680542. Accuracy: 10
Epoch: 9. Loss: 2.291691780090332. Accuracy: 10
Epoch: 10. Loss: 2.302030563354492. Accuracy: 10
Epoch: 11. Loss: 2.3215129375457764. Accuracy: 10
Epoch: 12. Loss: 2.302258014678955. Accuracy: 10
Epoch: 13. Loss: 2.2994210720062256. Accuracy: 10
Epoch: 14. Loss: 2.3233325481414795. Accuracy: 10
[ 0.09924230018397677 256 tensor(10) ]
Loss: 2.3233325481414795
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.001067983801839638

Epoch: 0. Loss: 0.32719606161117554. Accuracy: 82
Epoch: 1. Loss: 0.2685334086418152. Accuracy: 85
Epoch: 2. Loss: 0.2445177584886551. Accuracy: 87
Epoch: 3. Loss: 0.028092160820961. Accuracy: 88
Epoch: 4. Loss: 0.06078682839870453. Accuracy: 90
Epoch: 5. Loss: 0.06733791530132294. Accuracy: 90
Epoch: 6. Loss: 0.08034716546535492. Accuracy: 91
Epoch: 7. Loss: 0.035186320543289185. Accuracy: 90
Epoch: 8. Loss: 0.46296751499176025. Accuracy: 91
Epoch: 9. Loss: 0.03294620290398598. Accuracy: 91
Epoch: 10. Loss: 0.02146189659833908. Accuracy: 91
Epoch: 11. Loss: 0.0008354485034942627. Accuracy: 91
Epoch: 12. Loss: 0.34974390268325806. Accuracy: 90
Epoch: 13. Loss: 0.026081137359142303. Accuracy: 91
Epoch: 14. Loss: 0.05014555901288986. Accuracy: 91
[ 0.001067983801839638 64 tensor(91) ]
Loss: 0.05014555901288986
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.08398143387272095

Epoch: 0. Loss: 2.3243184089660645. Accuracy: 10
Epoch: 1. Loss: 2.2996296882629395. Accuracy: 10
Epoch: 2. Loss: 2.297584056854248. Accuracy: 10
Epoch: 3. Loss: 2.2995691299438477. Accuracy: 10
Epoch: 4. Loss: 2.304236888885498. Accuracy: 10
Epoch: 5. Loss: 2.298046827316284. Accuracy: 10
Epoch: 6. Loss: 2.252782106399536. Accuracy: 10
Epoch: 7. Loss: 2.3023300170898438. Accuracy: 10
Epoch: 8. Loss: 2.333247184753418. Accuracy: 10
Epoch: 9. Loss: 2.3342044353485107. Accuracy: 10
Epoch: 10. Loss: 2.284034252166748. Accuracy: 10
Epoch: 11. Loss: 2.322584867477417. Accuracy: 10
Epoch: 12. Loss: 2.3302721977233887. Accuracy: 10
Epoch: 13. Loss: 2.2671403884887695. Accuracy: 10
Epoch: 14. Loss: 2.36491322517395. Accuracy: 10
[ 0.08398143387272095 32 tensor(10) ]
Loss: 2.36491322517395
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0011351068039751697

Epoch: 0. Loss: 0.24768227338790894. Accuracy: 85
Epoch: 1. Loss: 0.10248373448848724. Accuracy: 88
Epoch: 2. Loss: 0.00855410099029541. Accuracy: 89
Epoch: 3. Loss: 0.04189090430736542. Accuracy: 90
Epoch: 4. Loss: 0.17357033491134644. Accuracy: 91
Epoch: 5. Loss: 0.09872938692569733. Accuracy: 91
Epoch: 6. Loss: 0.049227114766836166. Accuracy: 92
Epoch: 7. Loss: 0.13052156567573547. Accuracy: 91
Epoch: 8. Loss: 0.10909922420978546. Accuracy: 91
Epoch: 9. Loss: 0.014994010329246521. Accuracy: 92
Epoch: 10. Loss: 0.06879875808954239. Accuracy: 92
Epoch: 11. Loss: 0.06299948692321777. Accuracy: 92
Epoch: 12. Loss: 0.32944774627685547. Accuracy: 92
Epoch: 13. Loss: 0.0015698820352554321. Accuracy: 92
Epoch: 14. Loss: 0.005945801734924316. Accuracy: 92
[ 0.0011351068039751697 32 tensor(92) ]
Loss: 0.005945801734924316
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.047345615396163734

Epoch: 0. Loss: 2.2900054454803467. Accuracy: 10
Epoch: 1. Loss: 2.3073432445526123. Accuracy: 10
Epoch: 2. Loss: 2.288304567337036. Accuracy: 10
Epoch: 3. Loss: 2.303004264831543. Accuracy: 10
Epoch: 4. Loss: 2.3573532104492188. Accuracy: 10
Epoch: 5. Loss: 2.364966869354248. Accuracy: 10
Epoch: 6. Loss: 2.309978485107422. Accuracy: 10
Epoch: 7. Loss: 2.3199193477630615. Accuracy: 10
Epoch: 8. Loss: 2.3207895755767822. Accuracy: 10
Epoch: 9. Loss: 2.309065341949463. Accuracy: 10
Epoch: 10. Loss: 2.3219175338745117. Accuracy: 10
Epoch: 11. Loss: 2.308164119720459. Accuracy: 10
Epoch: 12. Loss: 2.3504810333251953. Accuracy: 10
Epoch: 13. Loss: 2.3068881034851074. Accuracy: 10
Epoch: 14. Loss: 2.3709781169891357. Accuracy: 10
[ 0.047345615396163734 32 tensor(10) ]
Loss: 2.3709781169891357
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.005325956961742072

Epoch: 0. Loss: 0.17875653505325317. Accuracy: 85
Epoch: 1. Loss: 0.2401210218667984. Accuracy: 87
Epoch: 2. Loss: 0.25777408480644226. Accuracy: 87
Epoch: 3. Loss: 0.1337716430425644. Accuracy: 88
Epoch: 4. Loss: 0.19534368813037872. Accuracy: 89
Epoch: 5. Loss: 0.057519618421792984. Accuracy: 89
Epoch: 6. Loss: 0.14476972818374634. Accuracy: 90
Epoch: 7. Loss: 0.04989251494407654. Accuracy: 90
Epoch: 8. Loss: 0.11502260714769363. Accuracy: 90
Epoch: 9. Loss: 0.10212314128875732. Accuracy: 89
Epoch: 10. Loss: 0.14055083692073822. Accuracy: 90
Epoch: 11. Loss: 0.17367666959762573. Accuracy: 90
Epoch: 12. Loss: 0.11356455087661743. Accuracy: 90
Epoch: 13. Loss: 0.04935507848858833. Accuracy: 91
Epoch: 14. Loss: 0.16511739790439606. Accuracy: 90
[ 0.005325956961742072 128 tensor(90) ]
Loss: 0.16511739790439606
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.021102839450985372

Epoch: 0. Loss: 0.35151347517967224. Accuracy: 84
Epoch: 1. Loss: 0.23922817409038544. Accuracy: 87
Epoch: 2. Loss: 0.1779240369796753. Accuracy: 87
Epoch: 3. Loss: 0.1027388945221901. Accuracy: 86
Epoch: 4. Loss: 0.1810818314552307. Accuracy: 88
Epoch: 5. Loss: 0.15475890040397644. Accuracy: 88
Epoch: 6. Loss: 0.22461657226085663. Accuracy: 87
Epoch: 7. Loss: 0.1724863201379776. Accuracy: 87
Epoch: 8. Loss: 0.1726691573858261. Accuracy: 87
Epoch: 9. Loss: 0.11514562368392944. Accuracy: 87
Epoch: 10. Loss: 0.17291921377182007. Accuracy: 86
Epoch: 11. Loss: 0.08364216238260269. Accuracy: 87
Epoch: 12. Loss: 0.07015188038349152. Accuracy: 88
Epoch: 13. Loss: 0.12400829792022705. Accuracy: 89
Epoch: 14. Loss: 0.20914721488952637. Accuracy: 88
[ 0.021102839450985372 128 tensor(88) ]
Loss: 0.20914721488952637
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.00015773997251616317

Epoch: 0. Loss: 0.4684554636478424. Accuracy: 69
Epoch: 1. Loss: 0.22970829904079437. Accuracy: 77
Epoch: 2. Loss: 0.3239952027797699. Accuracy: 80
Epoch: 3. Loss: 0.29991576075553894. Accuracy: 82
Epoch: 4. Loss: 0.11203478276729584. Accuracy: 84
Epoch: 5. Loss: 0.31785959005355835. Accuracy: 84
Epoch: 6. Loss: 0.1055690348148346. Accuracy: 85
Epoch: 7. Loss: 0.1344384253025055. Accuracy: 86
Epoch: 8. Loss: 0.1357363611459732. Accuracy: 86
Epoch: 9. Loss: 0.10203374177217484. Accuracy: 86
Epoch: 10. Loss: 0.1303522288799286. Accuracy: 88
Epoch: 11. Loss: 0.2057381570339203. Accuracy: 87
Epoch: 12. Loss: 0.3148033618927002. Accuracy: 88
Epoch: 13. Loss: 0.030970757827162743. Accuracy: 89
Epoch: 14. Loss: 0.12076032906770706. Accuracy: 89
[ 0.00015773997251616317 32 tensor(89) ]
Loss: 0.12076032906770706
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.010081436736581063

Epoch: 0. Loss: 0.13615527749061584. Accuracy: 85
Epoch: 1. Loss: 0.11295657604932785. Accuracy: 86
Epoch: 2. Loss: 0.22068317234516144. Accuracy: 87
Epoch: 3. Loss: 0.11076945066452026. Accuracy: 88
Epoch: 4. Loss: 0.07189930975437164. Accuracy: 88
Epoch: 5. Loss: 0.6332674026489258. Accuracy: 87
Epoch: 6. Loss: 0.2530736029148102. Accuracy: 88
Epoch: 7. Loss: 0.10524555295705795. Accuracy: 88
Epoch: 8. Loss: 0.022847354412078857. Accuracy: 88
Epoch: 9. Loss: 0.27905410528182983. Accuracy: 89
Epoch: 10. Loss: 0.13155792653560638. Accuracy: 88
Epoch: 11. Loss: 0.08767718076705933. Accuracy: 88
Epoch: 12. Loss: 0.16437900066375732. Accuracy: 88
Epoch: 13. Loss: 0.27825695276260376. Accuracy: 89
Epoch: 14. Loss: 0.45297807455062866. Accuracy: 88
[ 0.010081436736581063 32 tensor(88) ]
Loss: 0.45297807455062866
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.0034328145599156028

Epoch: 0. Loss: 0.24594968557357788. Accuracy: 85
Epoch: 1. Loss: 0.21266227960586548. Accuracy: 88
Epoch: 2. Loss: 0.09116904437541962. Accuracy: 90
Epoch: 3. Loss: 0.019773215055465698. Accuracy: 90
Epoch: 4. Loss: 0.09501819312572479. Accuracy: 90
Epoch: 5. Loss: 0.18018227815628052. Accuracy: 90
Epoch: 6. Loss: 0.10826367139816284. Accuracy: 90
Epoch: 7. Loss: 0.02158357948064804. Accuracy: 90
Epoch: 8. Loss: 0.18709391355514526. Accuracy: 91
Epoch: 9. Loss: 0.13633865118026733. Accuracy: 90
Epoch: 10. Loss: 0.008160561323165894. Accuracy: 90
Epoch: 11. Loss: 0.02979595959186554. Accuracy: 91
Epoch: 12. Loss: 0.08694145828485489. Accuracy: 90
Epoch: 13. Loss: 0.04685769975185394. Accuracy: 91
Epoch: 14. Loss: 0.08714365214109421. Accuracy: 91
[ 0.0034328145599156028 64 tensor(91) ]
Loss: 0.08714365214109421
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.009297464631283758

Epoch: 0. Loss: 0.12163882702589035. Accuracy: 87
Epoch: 1. Loss: 0.1264335811138153. Accuracy: 89
Epoch: 2. Loss: 0.8728733062744141. Accuracy: 88
Epoch: 3. Loss: 0.02063431590795517. Accuracy: 89
Epoch: 4. Loss: 0.07835142314434052. Accuracy: 88
Epoch: 5. Loss: 0.14679889380931854. Accuracy: 89
Epoch: 6. Loss: 0.06959323585033417. Accuracy: 89
Epoch: 7. Loss: 0.1751421093940735. Accuracy: 89
Epoch: 8. Loss: 0.06182275712490082. Accuracy: 89
Epoch: 9. Loss: 0.05315522849559784. Accuracy: 88
Epoch: 10. Loss: 0.0961284413933754. Accuracy: 89
Epoch: 11. Loss: 0.12814170122146606. Accuracy: 89
Epoch: 12. Loss: 0.01107451319694519. Accuracy: 89
Epoch: 13. Loss: 0.6145652532577515. Accuracy: 89
Epoch: 14. Loss: 0.24425475299358368. Accuracy: 88
[ 0.009297464631283758 64 tensor(88) ]
Loss: 0.24425475299358368
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.013935861839958636

Epoch: 0. Loss: 0.4800091087818146. Accuracy: 82
Epoch: 1. Loss: 0.41563984751701355. Accuracy: 85
Epoch: 2. Loss: 0.13706931471824646. Accuracy: 84
Epoch: 3. Loss: 0.11379482597112656. Accuracy: 85
Epoch: 4. Loss: 0.18679456412792206. Accuracy: 84
Epoch: 5. Loss: 0.12600845098495483. Accuracy: 84
Epoch: 6. Loss: 0.662185549736023. Accuracy: 85
Epoch: 7. Loss: 0.1291075199842453. Accuracy: 85
Epoch: 8. Loss: 0.4638369083404541. Accuracy: 85
Epoch: 9. Loss: 0.6400821208953857. Accuracy: 85
Epoch: 10. Loss: 0.14716382324695587. Accuracy: 86
Epoch: 11. Loss: 0.20552010834217072. Accuracy: 85
Epoch: 12. Loss: 0.03683312237262726. Accuracy: 86
Epoch: 13. Loss: 0.322722852230072. Accuracy: 84
Epoch: 14. Loss: 0.2354736328125. Accuracy: 85
[ 0.013935861839958636 64 tensor(85) ]
Loss: 0.2354736328125
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.0035228219322844985

Epoch: 0. Loss: 0.2688709795475006. Accuracy: 81
Epoch: 1. Loss: 0.10429660230875015. Accuracy: 87
Epoch: 2. Loss: 0.21989910304546356. Accuracy: 89
Epoch: 3. Loss: 0.1979912370443344. Accuracy: 88
Epoch: 4. Loss: 0.16912920773029327. Accuracy: 89
Epoch: 5. Loss: 0.09939154237508774. Accuracy: 91
Epoch: 6. Loss: 0.04617216810584068. Accuracy: 90
Epoch: 7. Loss: 0.20994313061237335. Accuracy: 91
Epoch: 8. Loss: 0.05061161890625954. Accuracy: 91
Epoch: 9. Loss: 0.10426738113164902. Accuracy: 91
Epoch: 10. Loss: 0.05221180617809296. Accuracy: 90
Epoch: 11. Loss: 0.043275415897369385. Accuracy: 91
Epoch: 12. Loss: 0.061608415096998215. Accuracy: 91
Epoch: 13. Loss: 0.023903580382466316. Accuracy: 91
Epoch: 14. Loss: 0.035073887556791306. Accuracy: 91
[ 0.0035228219322844985 256 tensor(91) ]
Loss: 0.035073887556791306
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.06067574928459171

Epoch: 0. Loss: 2.3379781246185303. Accuracy: 10
Epoch: 1. Loss: 2.3057374954223633. Accuracy: 10
Epoch: 2. Loss: 2.3339526653289795. Accuracy: 10
Epoch: 3. Loss: 2.323467969894409. Accuracy: 10
Epoch: 4. Loss: 2.3185670375823975. Accuracy: 10
Epoch: 5. Loss: 2.3589463233947754. Accuracy: 10
Epoch: 6. Loss: 2.3152472972869873. Accuracy: 10
Epoch: 7. Loss: 2.297097682952881. Accuracy: 10
Epoch: 8. Loss: 2.2657768726348877. Accuracy: 10
Epoch: 9. Loss: 2.3096094131469727. Accuracy: 10
Epoch: 10. Loss: 2.303131341934204. Accuracy: 10
Epoch: 11. Loss: 2.3140084743499756. Accuracy: 10
Epoch: 12. Loss: 2.360974073410034. Accuracy: 10
Epoch: 13. Loss: 2.3548481464385986. Accuracy: 10
Epoch: 14. Loss: 2.3298070430755615. Accuracy: 10
[ 0.06067574928459171 32 tensor(10) ]
Loss: 2.3298070430755615
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.0028674141462326115

Epoch: 0. Loss: 0.11426258087158203. Accuracy: 84
Epoch: 1. Loss: 0.20209239423274994. Accuracy: 87
Epoch: 2. Loss: 0.274135947227478. Accuracy: 89
Epoch: 3. Loss: 0.049712177366018295. Accuracy: 90
Epoch: 4. Loss: 0.05847061797976494. Accuracy: 91
Epoch: 5. Loss: 0.1429184079170227. Accuracy: 91
Epoch: 6. Loss: 0.03724927455186844. Accuracy: 90
Epoch: 7. Loss: 0.08968904614448547. Accuracy: 91
Epoch: 8. Loss: 0.04626733064651489. Accuracy: 90
Epoch: 9. Loss: 0.07528705894947052. Accuracy: 91
Epoch: 10. Loss: 0.009230871684849262. Accuracy: 90
Epoch: 11. Loss: 0.027755295857787132. Accuracy: 91
Epoch: 12. Loss: 0.03461204096674919. Accuracy: 92
Epoch: 13. Loss: 0.0783785954117775. Accuracy: 92
Epoch: 14. Loss: 0.03217535838484764. Accuracy: 92
[ 0.0028674141462326115 128 tensor(92) ]
Loss: 0.03217535838484764
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.0034940545262981126

Epoch: 0. Loss: 0.0709872767329216. Accuracy: 85
Epoch: 1. Loss: 0.20067329704761505. Accuracy: 89
Epoch: 2. Loss: 0.09125649183988571. Accuracy: 90
Epoch: 3. Loss: 0.13282781839370728. Accuracy: 90
Epoch: 4. Loss: 0.11543092876672745. Accuracy: 91
Epoch: 5. Loss: 0.07407630234956741. Accuracy: 91
Epoch: 6. Loss: 0.15564937889575958. Accuracy: 92
Epoch: 7. Loss: 0.1720844954252243. Accuracy: 92
Epoch: 8. Loss: 0.06757508218288422. Accuracy: 91
Epoch: 9. Loss: 0.05703296139836311. Accuracy: 91
Epoch: 10. Loss: 0.04911896958947182. Accuracy: 91
Epoch: 11. Loss: 0.046337857842445374. Accuracy: 92
Epoch: 12. Loss: 0.08214384317398071. Accuracy: 92
Epoch: 13. Loss: 0.12593139708042145. Accuracy: 92
Epoch: 14. Loss: 0.0400647334754467. Accuracy: 92
[ 0.0034940545262981126 128 tensor(92) ]
Loss: 0.0400647334754467
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0014137797336664056

Epoch: 0. Loss: 0.2170235812664032. Accuracy: 86
Epoch: 1. Loss: 0.1281733214855194. Accuracy: 87
Epoch: 2. Loss: 0.13647469878196716. Accuracy: 90
Epoch: 3. Loss: 0.14387473464012146. Accuracy: 90
Epoch: 4. Loss: 0.02893604338169098. Accuracy: 91
Epoch: 5. Loss: 0.09199786186218262. Accuracy: 91
Epoch: 6. Loss: 0.006342992186546326. Accuracy: 91
Epoch: 7. Loss: 0.13967540860176086. Accuracy: 91
Epoch: 8. Loss: 0.02283516526222229. Accuracy: 91
Epoch: 9. Loss: 0.030059829354286194. Accuracy: 91
Epoch: 10. Loss: 0.0024744421243667603. Accuracy: 92
Epoch: 11. Loss: 0.006011240184307098. Accuracy: 91
Epoch: 12. Loss: 0.0030912980437278748. Accuracy: 91
Epoch: 13. Loss: 0.03212188556790352. Accuracy: 92
Epoch: 14. Loss: 0.0021932870149612427. Accuracy: 92
[ 0.0014137797336664056 32 tensor(92) ]
Loss: 0.0021932870149612427
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0013962979803087401

Epoch: 0. Loss: 0.39548224210739136. Accuracy: 85
Epoch: 1. Loss: 0.3239973485469818. Accuracy: 89
Epoch: 2. Loss: 0.11485940217971802. Accuracy: 89
Epoch: 3. Loss: 0.00852677971124649. Accuracy: 90
Epoch: 4. Loss: 0.04468401521444321. Accuracy: 91
Epoch: 5. Loss: 0.02195335552096367. Accuracy: 91
Epoch: 6. Loss: 0.070564866065979. Accuracy: 91
Epoch: 7. Loss: 0.0943419337272644. Accuracy: 92
Epoch: 8. Loss: 0.06313608586788177. Accuracy: 91
Epoch: 9. Loss: 0.10444242507219315. Accuracy: 92
Epoch: 10. Loss: 0.05872529000043869. Accuracy: 91
Epoch: 11. Loss: 0.024297066032886505. Accuracy: 91
Epoch: 12. Loss: 0.11074542254209518. Accuracy: 92
Epoch: 13. Loss: 0.01854092627763748. Accuracy: 92
Epoch: 14. Loss: 0.05735061690211296. Accuracy: 92
[ 0.0013962979803087401 32 tensor(92) ]
Loss: 0.05735061690211296
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.08515027959924616

Epoch: 0. Loss: 2.318646192550659. Accuracy: 10
Epoch: 1. Loss: 2.277268886566162. Accuracy: 10
Epoch: 2. Loss: 2.266665458679199. Accuracy: 10
Epoch: 3. Loss: 2.314030647277832. Accuracy: 10
Epoch: 4. Loss: 2.314854145050049. Accuracy: 10
Epoch: 5. Loss: 2.332625150680542. Accuracy: 10
Epoch: 6. Loss: 2.3564138412475586. Accuracy: 10
Epoch: 7. Loss: 2.3225295543670654. Accuracy: 10
Epoch: 8. Loss: 2.32966947555542. Accuracy: 10
Epoch: 9. Loss: 2.3197999000549316. Accuracy: 10
Epoch: 10. Loss: 2.3028132915496826. Accuracy: 10
Epoch: 11. Loss: 2.288367986679077. Accuracy: 10
Epoch: 12. Loss: 2.328366756439209. Accuracy: 10
Epoch: 13. Loss: 2.288970470428467. Accuracy: 10
Epoch: 14. Loss: 2.354543685913086. Accuracy: 10
[ 0.08515027959924616 32 tensor(10) ]
Loss: 2.354543685913086
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.08493858744593881

Epoch: 0. Loss: 0.9933896064758301. Accuracy: 57
Epoch: 1. Loss: 0.8971149325370789. Accuracy: 54
Epoch: 2. Loss: 0.9905230402946472. Accuracy: 57
Epoch: 3. Loss: 0.6821034550666809. Accuracy: 56
Epoch: 4. Loss: 0.8152079582214355. Accuracy: 55
Epoch: 5. Loss: 0.8622403740882874. Accuracy: 56
Epoch: 6. Loss: 0.8751122355461121. Accuracy: 57
Epoch: 7. Loss: 1.7287653684616089. Accuracy: 18
Epoch: 8. Loss: 0.8595352172851562. Accuracy: 56
Epoch: 9. Loss: 0.8293867707252502. Accuracy: 57
Epoch: 10. Loss: 0.6781091094017029. Accuracy: 56
Epoch: 11. Loss: 0.8329619765281677. Accuracy: 57
Epoch: 12. Loss: 0.8876672387123108. Accuracy: 55
Epoch: 13. Loss: 2.314549446105957. Accuracy: 10
Epoch: 14. Loss: 2.315124273300171. Accuracy: 10
[ 0.08493858744593881 128 tensor(10) ]
Loss: 2.315124273300171
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.006420217713854331

Epoch: 0. Loss: 0.24898560345172882. Accuracy: 84
Epoch: 1. Loss: 0.11890489608049393. Accuracy: 89
Epoch: 2. Loss: 0.238480344414711. Accuracy: 90
Epoch: 3. Loss: 0.02707410790026188. Accuracy: 90
Epoch: 4. Loss: 0.09781986474990845. Accuracy: 91
Epoch: 5. Loss: 0.03464891016483307. Accuracy: 92
Epoch: 6. Loss: 0.05237099900841713. Accuracy: 92
Epoch: 7. Loss: 0.10692588239908218. Accuracy: 92
Epoch: 8. Loss: 0.048701781779527664. Accuracy: 92
Epoch: 9. Loss: 0.0715937539935112. Accuracy: 92
Epoch: 10. Loss: 0.05047148838639259. Accuracy: 92
Epoch: 11. Loss: 0.0432952456176281. Accuracy: 91
Epoch: 12. Loss: 0.01233768928796053. Accuracy: 92
Epoch: 13. Loss: 0.06296446919441223. Accuracy: 91
Epoch: 14. Loss: 0.10563019663095474. Accuracy: 93
[ 0.006420217713854331 256 tensor(93) ]
Loss: 0.10563019663095474
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.005677442641871205

Epoch: 0. Loss: 0.337592214345932. Accuracy: 83
Epoch: 1. Loss: 0.14843635261058807. Accuracy: 88
Epoch: 2. Loss: 0.10845118016004562. Accuracy: 89
Epoch: 3. Loss: 0.2255008965730667. Accuracy: 89
Epoch: 4. Loss: 0.1843140870332718. Accuracy: 91
Epoch: 5. Loss: 0.10369089990854263. Accuracy: 90
Epoch: 6. Loss: 0.042612865567207336. Accuracy: 91
Epoch: 7. Loss: 0.17216141521930695. Accuracy: 92
Epoch: 8. Loss: 0.06631004810333252. Accuracy: 91
Epoch: 9. Loss: 0.04898447170853615. Accuracy: 91
Epoch: 10. Loss: 0.09899226576089859. Accuracy: 91
Epoch: 11. Loss: 0.011612892150878906. Accuracy: 91
Epoch: 12. Loss: 0.09541946649551392. Accuracy: 91
Epoch: 13. Loss: 0.10139463096857071. Accuracy: 91
Epoch: 14. Loss: 0.14755992591381073. Accuracy: 91
[ 0.005677442641871205 256 tensor(91) ]
Loss: 0.14755992591381073
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0016638216321535756

Epoch: 0. Loss: 0.05972505360841751. Accuracy: 85
Epoch: 1. Loss: 0.3601665794849396. Accuracy: 87
Epoch: 2. Loss: 0.02254553884267807. Accuracy: 90
Epoch: 3. Loss: 0.02042613923549652. Accuracy: 90
Epoch: 4. Loss: 0.167941614985466. Accuracy: 90
Epoch: 5. Loss: 0.033858127892017365. Accuracy: 90
Epoch: 6. Loss: 0.007295206189155579. Accuracy: 90
Epoch: 7. Loss: 0.03549933433532715. Accuracy: 92
Epoch: 8. Loss: 0.14672289788722992. Accuracy: 91
Epoch: 9. Loss: 0.12324771285057068. Accuracy: 91
Epoch: 10. Loss: 0.008247651159763336. Accuracy: 90
Epoch: 11. Loss: 0.06781909614801407. Accuracy: 91
Epoch: 12. Loss: 0.020106647163629532. Accuracy: 91
Epoch: 13. Loss: 0.15381872653961182. Accuracy: 91
Epoch: 14. Loss: 0.003865353763103485. Accuracy: 92
[ 0.0016638216321535756 32 tensor(92) ]
Loss: 0.003865353763103485
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.0030361138199290266

Epoch: 0. Loss: 0.3630851209163666. Accuracy: 82
Epoch: 1. Loss: 0.2626509368419647. Accuracy: 86
Epoch: 2. Loss: 0.17043475806713104. Accuracy: 88
Epoch: 3. Loss: 0.12390578538179398. Accuracy: 89
Epoch: 4. Loss: 0.16114191710948944. Accuracy: 89
Epoch: 5. Loss: 0.0678887888789177. Accuracy: 90
Epoch: 6. Loss: 0.1322312355041504. Accuracy: 90
Epoch: 7. Loss: 0.05814250931143761. Accuracy: 90
Epoch: 8. Loss: 0.07023616880178452. Accuracy: 91
Epoch: 9. Loss: 0.05559011176228523. Accuracy: 91
Epoch: 10. Loss: 0.036812879145145416. Accuracy: 90
Epoch: 11. Loss: 0.06584829092025757. Accuracy: 91
Epoch: 12. Loss: 0.09326908737421036. Accuracy: 91
Epoch: 13. Loss: 0.03473218157887459. Accuracy: 91
Epoch: 14. Loss: 0.03248339891433716. Accuracy: 91
[ 0.0030361138199290266 256 tensor(91) ]
Loss: 0.03248339891433716
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.0551610074711774

Epoch: 0. Loss: 2.30047345161438. Accuracy: 10
Epoch: 1. Loss: 2.3175575733184814. Accuracy: 10
Epoch: 2. Loss: 2.301881790161133. Accuracy: 10
Epoch: 3. Loss: 2.300821542739868. Accuracy: 10
Epoch: 4. Loss: 2.3137383460998535. Accuracy: 10
Epoch: 5. Loss: 2.303154230117798. Accuracy: 10
Epoch: 6. Loss: 2.3103857040405273. Accuracy: 10
Epoch: 7. Loss: 2.317356824874878. Accuracy: 10
Epoch: 8. Loss: 2.304277181625366. Accuracy: 10
Epoch: 9. Loss: 2.2993409633636475. Accuracy: 10
Epoch: 10. Loss: 2.3067023754119873. Accuracy: 10
Epoch: 11. Loss: 2.2994611263275146. Accuracy: 10
Epoch: 12. Loss: 2.3036701679229736. Accuracy: 10
Epoch: 13. Loss: 2.302903413772583. Accuracy: 10
Epoch: 14. Loss: 2.3072140216827393. Accuracy: 10
[ 0.0551610074711774 256 tensor(10) ]
Loss: 2.3072140216827393
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.015557455889033898

Epoch: 0. Loss: 0.14362943172454834. Accuracy: 82
Epoch: 1. Loss: 0.0931234285235405. Accuracy: 85
Epoch: 2. Loss: 0.14804960787296295. Accuracy: 84
Epoch: 3. Loss: 0.20120219886302948. Accuracy: 86
Epoch: 4. Loss: 0.15241427719593048. Accuracy: 85
Epoch: 5. Loss: 0.12887589633464813. Accuracy: 87
Epoch: 6. Loss: 0.3222631514072418. Accuracy: 86
Epoch: 7. Loss: 0.27156195044517517. Accuracy: 86
Epoch: 8. Loss: 0.31448110938072205. Accuracy: 86
Epoch: 9. Loss: 0.2362499088048935. Accuracy: 85
Epoch: 10. Loss: 0.0661645457148552. Accuracy: 86
Epoch: 11. Loss: 0.13446985185146332. Accuracy: 86
Epoch: 12. Loss: 0.1664765179157257. Accuracy: 87
Epoch: 13. Loss: 0.08455505967140198. Accuracy: 86
Epoch: 14. Loss: 0.13413767516613007. Accuracy: 86
[ 0.015557455889033898 128 tensor(86) ]
Loss: 0.13413767516613007
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0012832703857225754

Epoch: 0. Loss: 0.20078352093696594. Accuracy: 86
Epoch: 1. Loss: 0.05793939158320427. Accuracy: 88
Epoch: 2. Loss: 0.1329672783613205. Accuracy: 89
Epoch: 3. Loss: 0.11204502731561661. Accuracy: 90
Epoch: 4. Loss: 0.02736787497997284. Accuracy: 91
Epoch: 5. Loss: 0.10039401054382324. Accuracy: 90
Epoch: 6. Loss: 0.2920991778373718. Accuracy: 91
Epoch: 7. Loss: 0.01238086074590683. Accuracy: 91
Epoch: 8. Loss: 0.11424187570810318. Accuracy: 91
Epoch: 9. Loss: 0.0026680678129196167. Accuracy: 92
Epoch: 10. Loss: 0.20238235592842102. Accuracy: 91
Epoch: 11. Loss: 0.0006801635026931763. Accuracy: 91
Epoch: 12. Loss: 0.07405988872051239. Accuracy: 92
Epoch: 13. Loss: 0.03580524027347565. Accuracy: 91
Epoch: 14. Loss: 0.012439802289009094. Accuracy: 91
[ 0.0012832703857225754 32 tensor(91) ]
Loss: 0.012439802289009094
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0012669696504505287

Epoch: 0. Loss: 0.036327995359897614. Accuracy: 85
Epoch: 1. Loss: 0.012095898389816284. Accuracy: 88
Epoch: 2. Loss: 0.11009668558835983. Accuracy: 90
Epoch: 3. Loss: 0.011516116559505463. Accuracy: 91
Epoch: 4. Loss: 0.04323846101760864. Accuracy: 91
Epoch: 5. Loss: 0.023936327546834946. Accuracy: 92
Epoch: 6. Loss: 0.05590450391173363. Accuracy: 92
Epoch: 7. Loss: 0.01430857926607132. Accuracy: 92
Epoch: 8. Loss: 0.011722695082426071. Accuracy: 92
Epoch: 9. Loss: 0.02198094129562378. Accuracy: 91
Epoch: 10. Loss: 0.036149583756923676. Accuracy: 92
Epoch: 11. Loss: 0.0943099856376648. Accuracy: 91
Epoch: 12. Loss: 0.044756580144166946. Accuracy: 92
Epoch: 13. Loss: 0.0027666687965393066. Accuracy: 92
Epoch: 14. Loss: 0.029304996132850647. Accuracy: 92
[ 0.0012669696504505287 32 tensor(92) ]
Loss: 0.029304996132850647
Running: Configuration:
  batch_size, Value: 32
  lr, Value: 0.0015419402701343594

Epoch: 0. Loss: 0.23121419548988342. Accuracy: 86
Epoch: 1. Loss: 0.5098445415496826. Accuracy: 88
Epoch: 2. Loss: 0.03866724669933319. Accuracy: 90
Epoch: 3. Loss: 0.035987935960292816. Accuracy: 91
Epoch: 4. Loss: 0.020911753177642822. Accuracy: 90
Epoch: 5. Loss: 0.07803896814584732. Accuracy: 91
Epoch: 6. Loss: 0.06336303055286407. Accuracy: 92
Epoch: 7. Loss: 0.2010902464389801. Accuracy: 91
Epoch: 8. Loss: 0.0407460555434227. Accuracy: 92
Epoch: 9. Loss: 0.001340709626674652. Accuracy: 92
Epoch: 10. Loss: 0.009710535407066345. Accuracy: 92
Epoch: 11. Loss: 0.17487534880638123. Accuracy: 91
Epoch: 12. Loss: 0.016171850264072418. Accuracy: 91
Epoch: 13. Loss: 0.08073725551366806. Accuracy: 91
Epoch: 14. Loss: 0.01159106194972992. Accuracy: 91
[ 0.0015419402701343594 32 tensor(91) ]
Loss: 0.01159106194972992
Running: Configuration:
  batch_size, Value: 256
  lr, Value: 0.033150925607741626

Epoch: 0. Loss: 0.6204259991645813. Accuracy: 63
Epoch: 1. Loss: 0.683868944644928. Accuracy: 67
Epoch: 2. Loss: 0.6148325800895691. Accuracy: 66
Epoch: 3. Loss: 0.662665843963623. Accuracy: 65
Epoch: 4. Loss: 0.7402849793434143. Accuracy: 66
Epoch: 5. Loss: 0.5910471081733704. Accuracy: 67
Epoch: 6. Loss: 0.570582926273346. Accuracy: 66
Epoch: 7. Loss: 0.869954526424408. Accuracy: 67
Epoch: 8. Loss: 0.5782443284988403. Accuracy: 67
Epoch: 9. Loss: 0.44241225719451904. Accuracy: 67
Epoch: 10. Loss: 0.5883082747459412. Accuracy: 65
Epoch: 11. Loss: 0.49351343512535095. Accuracy: 67
Epoch: 12. Loss: 0.741064727306366. Accuracy: 66
Epoch: 13. Loss: 0.73746657371521. Accuracy: 67
Epoch: 14. Loss: 0.41672396659851074. Accuracy: 68
[ 0.033150925607741626 256 tensor(68) ]
Loss: 0.41672396659851074
Running: Configuration:
  batch_size, Value: 128
  lr, Value: 0.051300886284833036

Epoch: 0. Loss: 1.3125017881393433. Accuracy: 52
Epoch: 1. Loss: 1.0944706201553345. Accuracy: 52
Epoch: 2. Loss: 1.2100167274475098. Accuracy: 51
Epoch: 3. Loss: 1.3131428956985474. Accuracy: 51
Epoch: 4. Loss: 1.2032817602157593. Accuracy: 52
Epoch: 5. Loss: 1.0978896617889404. Accuracy: 53
Epoch: 6. Loss: 0.9624590277671814. Accuracy: 58
Epoch: 7. Loss: 0.8120518326759338. Accuracy: 58
Epoch: 8. Loss: 0.8162550330162048. Accuracy: 56
Epoch: 9. Loss: 1.3168851137161255. Accuracy: 58
Epoch: 10. Loss: 0.9732232689857483. Accuracy: 56
Epoch: 11. Loss: 0.6567972898483276. Accuracy: 60
Epoch: 12. Loss: 1.0330981016159058. Accuracy: 58
Epoch: 13. Loss: 0.73585444688797. Accuracy: 58
Epoch: 14. Loss: 0.8734042048454285. Accuracy: 60
[ 0.051300886284833036 128 tensor(60) ]
Loss: 0.8734042048454285
incumbent configuration:
Running: Configuration:
  batch_size, Value: 64
  lr, Value: 0.0064434254058602985

Epoch: 0. Loss: 0.15389487147331238. Accuracy: 87
Epoch: 1. Loss: 0.11278344690799713. Accuracy: 89
Epoch: 2. Loss: 0.03506623953580856. Accuracy: 91
Epoch: 3. Loss: 0.16982503235340118. Accuracy: 91
Epoch: 4. Loss: 0.1119966208934784. Accuracy: 91
Epoch: 5. Loss: 0.20600582659244537. Accuracy: 90
Epoch: 6. Loss: 0.0807180106639862. Accuracy: 89
Epoch: 7. Loss: 0.1199866458773613. Accuracy: 91
Epoch: 8. Loss: 0.012155771255493164. Accuracy: 91
Epoch: 9. Loss: 0.02374337613582611. Accuracy: 91
Epoch: 10. Loss: 0.016481131315231323. Accuracy: 90
Epoch: 11. Loss: 0.18999993801116943. Accuracy: 91
Epoch: 12. Loss: 0.013209521770477295. Accuracy: 91
Epoch: 13. Loss: 0.026613399386405945. Accuracy: 90
Epoch: 14. Loss: 0.009865626692771912. Accuracy: 92
[ 0.0064434254058602985 64 tensor(92) ]
Loss: 0.009865626692771912
Optimized loss Value: 0.01