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Librarian Bot: Add base_model information to model (#2)
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
base_model: google/bert_uncased_L-2_H-128_A-2
model-index:
  - name: bert_uncased_L-2_H-128_A-2-nan-labels-new-longer
    results: []

bert_uncased_L-2_H-128_A-2-nan-labels-new-longer

This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 8.4563

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1000

Training results

Training Loss Epoch Step Validation Loss
6.445 1.0 14 6.4988
5.9033 2.0 28 6.4333
5.6732 3.0 42 6.4295
5.6525 4.0 56 6.3895
5.4781 5.0 70 6.3660
5.31 6.0 84 6.4213
5.1629 7.0 98 6.3842
5.1541 8.0 112 6.4043
5.0659 9.0 126 6.4686
4.8597 10.0 140 6.4760
4.983 11.0 154 6.4753
4.9563 12.0 168 6.4612
4.8113 13.0 182 6.5363
4.86 14.0 196 6.5400
4.8254 15.0 210 6.5595
4.8032 16.0 224 6.5575
4.7343 17.0 238 6.5832
4.835 18.0 252 6.5729
4.6986 19.0 266 6.5705
4.6607 20.0 280 6.6127
4.6594 21.0 294 6.6145
4.6936 22.0 308 6.6280
4.6328 23.0 322 6.6249
4.6668 24.0 336 6.6779
4.5523 25.0 350 6.6236
4.3964 26.0 364 6.6895
4.4736 27.0 378 6.6899
4.5163 28.0 392 6.6832
4.5136 29.0 406 6.7013
4.542 30.0 420 6.6983
4.4362 31.0 434 6.7516
4.4466 32.0 448 6.7302
4.4834 33.0 462 6.7404
4.4824 34.0 476 6.7525
4.4302 35.0 490 6.7623
4.5098 36.0 504 6.7622
4.396 37.0 518 6.8025
4.3747 38.0 532 6.7847
4.2892 39.0 546 6.8394
4.3897 40.0 560 6.8372
4.2554 41.0 574 6.7644
4.3336 42.0 588 6.7843
4.2943 43.0 602 6.7806
4.3001 44.0 616 6.7864
4.1161 45.0 630 6.8487
4.1357 46.0 644 6.8556
4.2713 47.0 658 6.7995
4.2779 48.0 672 6.8441
4.2564 49.0 686 6.8388
4.192 50.0 700 6.7896
4.1692 51.0 714 6.8261
4.2694 52.0 728 6.8535
4.2109 53.0 742 6.8533
4.1504 54.0 756 6.8946
4.1131 55.0 770 6.8696
4.1799 56.0 784 6.8739
4.1055 57.0 798 6.8651
4.0118 58.0 812 6.8689
4.176 59.0 826 6.8895
4.1773 60.0 840 6.8385
3.9761 61.0 854 6.8580
4.1002 62.0 868 6.8556
3.9164 63.0 882 6.9133
4.0154 64.0 896 6.8968
4.008 65.0 910 6.8973
4.0876 66.0 924 6.8768
3.9527 67.0 938 6.9413
3.9351 68.0 952 6.9106
4.0333 69.0 966 6.9012
3.896 70.0 980 6.9127
4.0042 71.0 994 6.9211
3.9151 72.0 1008 6.9585
3.9852 73.0 1022 6.9027
3.9913 74.0 1036 6.9333
3.8787 75.0 1050 6.9345
3.9729 76.0 1064 6.9165
3.9449 77.0 1078 6.9660
3.9416 78.0 1092 6.9462
3.9497 79.0 1106 6.9617
3.8797 80.0 1120 6.9356
3.8509 81.0 1134 6.9562
3.9021 82.0 1148 6.9400
3.8218 83.0 1162 7.0029
3.9301 84.0 1176 7.0166
3.7591 85.0 1190 6.9891
3.8889 86.0 1204 6.9830
3.8063 87.0 1218 6.9812
3.8556 88.0 1232 7.0051
3.7773 89.0 1246 6.9959
3.745 90.0 1260 7.0423
3.8139 91.0 1274 7.0781
3.7354 92.0 1288 7.0206
3.7696 93.0 1302 6.9731
3.73 94.0 1316 7.0572
3.7019 95.0 1330 7.0119
3.6302 96.0 1344 7.0238
3.675 97.0 1358 7.0348
3.746 98.0 1372 7.0385
3.7106 99.0 1386 7.0477
3.6545 100.0 1400 7.0762
3.7246 101.0 1414 7.0063
3.6707 102.0 1428 7.0343
3.7569 103.0 1442 7.0196
3.6785 104.0 1456 7.0255
3.7535 105.0 1470 7.0461
3.7011 106.0 1484 7.0381
3.6112 107.0 1498 7.0440
3.5981 108.0 1512 7.0831
3.6751 109.0 1526 7.0568
3.674 110.0 1540 7.0905
3.5554 111.0 1554 7.0955
3.5834 112.0 1568 7.0668
3.581 113.0 1582 7.0943
3.5548 114.0 1596 7.0490
3.6446 115.0 1610 7.1190
3.6142 116.0 1624 7.1366
3.5748 117.0 1638 7.1047
3.5447 118.0 1652 7.1332
3.6093 119.0 1666 7.1137
3.5694 120.0 1680 7.1010
3.4729 121.0 1694 7.1186
3.5373 122.0 1708 7.1258
3.6168 123.0 1722 7.1184
3.5654 124.0 1736 7.0982
3.4747 125.0 1750 7.0908
3.5098 126.0 1764 7.1134
3.6144 127.0 1778 7.1033
3.4529 128.0 1792 7.1376
3.4286 129.0 1806 7.1056
3.5095 130.0 1820 7.1148
3.4333 131.0 1834 7.1185
3.4879 132.0 1848 7.1704
3.4992 133.0 1862 7.1361
3.4738 134.0 1876 7.1597
3.4358 135.0 1890 7.1244
3.4648 136.0 1904 7.1762
3.3206 137.0 1918 7.1274
3.3579 138.0 1932 7.1208
3.3573 139.0 1946 7.1614
3.3504 140.0 1960 7.1241
3.4585 141.0 1974 7.1421
3.3757 142.0 1988 7.2070
3.3911 143.0 2002 7.1862
3.2857 144.0 2016 7.1925
3.3898 145.0 2030 7.2269
3.3297 146.0 2044 7.2391
3.3361 147.0 2058 7.1945
3.2097 148.0 2072 7.2095
3.4288 149.0 2086 7.1376
3.4156 150.0 2100 7.1984
3.187 151.0 2114 7.2243
3.3137 152.0 2128 7.2164
3.2102 153.0 2142 7.1742
3.2992 154.0 2156 7.2086
3.3271 155.0 2170 7.2281
3.3251 156.0 2184 7.2360
3.2512 157.0 2198 7.2302
3.2914 158.0 2212 7.2106
3.1992 159.0 2226 7.2322
3.3029 160.0 2240 7.2548
3.2309 161.0 2254 7.2132
3.1554 162.0 2268 7.2323
3.2555 163.0 2282 7.2133
3.3232 164.0 2296 7.2382
3.1486 165.0 2310 7.2681
3.2693 166.0 2324 7.2976
3.2643 167.0 2338 7.2274
3.2331 168.0 2352 7.3139
3.1568 169.0 2366 7.2261
3.1509 170.0 2380 7.3050
3.0284 171.0 2394 7.2823
3.2062 172.0 2408 7.2707
3.1281 173.0 2422 7.2902
3.1225 174.0 2436 7.2687
3.1591 175.0 2450 7.2865
3.1179 176.0 2464 7.2920
3.1785 177.0 2478 7.2559
3.2278 178.0 2492 7.2736
3.132 179.0 2506 7.3053
3.0466 180.0 2520 7.2746
3.1254 181.0 2534 7.2709
3.1826 182.0 2548 7.3136
3.1385 183.0 2562 7.3178
3.1387 184.0 2576 7.2538
3.0793 185.0 2590 7.2920
3.112 186.0 2604 7.3260
3.1013 187.0 2618 7.2720
3.1897 188.0 2632 7.2739
3.0557 189.0 2646 7.3047
3.1642 190.0 2660 7.3403
2.9943 191.0 2674 7.3406
3.0325 192.0 2688 7.2799
3.076 193.0 2702 7.2900
3.003 194.0 2716 7.3443
3.0765 195.0 2730 7.3862
2.9823 196.0 2744 7.3070
3.0833 197.0 2758 7.2606
3.0209 198.0 2772 7.3284
2.9679 199.0 2786 7.3877
3.0575 200.0 2800 7.3454
2.9928 201.0 2814 7.3847
3.092 202.0 2828 7.3738
2.976 203.0 2842 7.3941
3.0173 204.0 2856 7.3801
2.9659 205.0 2870 7.3725
3.0016 206.0 2884 7.3803
2.9815 207.0 2898 7.3499
3.0251 208.0 2912 7.3261
2.927 209.0 2926 7.3570
3.0193 210.0 2940 7.3972
3.0152 211.0 2954 7.3770
2.9104 212.0 2968 7.3326
2.9868 213.0 2982 7.3898
3.0097 214.0 2996 7.3658
3.0093 215.0 3010 7.3975
2.8546 216.0 3024 7.3948
2.8972 217.0 3038 7.3734
2.9641 218.0 3052 7.4320
2.9083 219.0 3066 7.3582
2.9185 220.0 3080 7.4126
3.0003 221.0 3094 7.3918
2.8599 222.0 3108 7.4171
2.8931 223.0 3122 7.4251
2.9109 224.0 3136 7.4426
2.9417 225.0 3150 7.4428
2.8274 226.0 3164 7.4145
2.921 227.0 3178 7.3492
2.7542 228.0 3192 7.4100
2.8775 229.0 3206 7.4288
2.7467 230.0 3220 7.4359
2.8301 231.0 3234 7.4715
2.7856 232.0 3248 7.4036
2.835 233.0 3262 7.4038
2.7665 234.0 3276 7.4919
2.8972 235.0 3290 7.4808
2.8768 236.0 3304 7.5259
2.9377 237.0 3318 7.4187
2.8489 238.0 3332 7.4590
2.8018 239.0 3346 7.4565
2.771 240.0 3360 7.4474
2.7378 241.0 3374 7.5119
2.822 242.0 3388 7.4734
2.8274 243.0 3402 7.4984
2.7732 244.0 3416 7.4829
2.7264 245.0 3430 7.4391
2.7764 246.0 3444 7.4456
2.7972 247.0 3458 7.4858
2.8231 248.0 3472 7.4760
2.778 249.0 3486 7.4380
2.7935 250.0 3500 7.4336
2.7348 251.0 3514 7.4970
2.7192 252.0 3528 7.4811
2.8108 253.0 3542 7.4547
2.837 254.0 3556 7.4830
2.6868 255.0 3570 7.5151
2.7789 256.0 3584 7.5115
2.7706 257.0 3598 7.5180
2.7904 258.0 3612 7.5158
2.7215 259.0 3626 7.5262
2.6876 260.0 3640 7.5114
2.7679 261.0 3654 7.5066
2.7742 262.0 3668 7.5035
2.6965 263.0 3682 7.4918
2.668 264.0 3696 7.5305
2.6808 265.0 3710 7.5238
2.6491 266.0 3724 7.5347
2.7307 267.0 3738 7.5175
2.6518 268.0 3752 7.5635
2.6685 269.0 3766 7.4899
2.671 270.0 3780 7.4855
2.596 271.0 3794 7.5518
2.6622 272.0 3808 7.5308
2.6684 273.0 3822 7.5955
2.6325 274.0 3836 7.5768
2.6334 275.0 3850 7.5202
2.6042 276.0 3864 7.6176
2.7439 277.0 3878 7.5369
2.6925 278.0 3892 7.5422
2.7106 279.0 3906 7.5629
2.6519 280.0 3920 7.5359
2.6044 281.0 3934 7.5619
2.6509 282.0 3948 7.5433
2.6777 283.0 3962 7.5573
2.6199 284.0 3976 7.5628
2.6685 285.0 3990 7.5710
2.6608 286.0 4004 7.6020
2.6579 287.0 4018 7.5780
2.5559 288.0 4032 7.5713
2.5091 289.0 4046 7.5912
2.6141 290.0 4060 7.6475
2.6832 291.0 4074 7.5865
2.5769 292.0 4088 7.6198
2.6432 293.0 4102 7.6058
2.5733 294.0 4116 7.5853
2.5782 295.0 4130 7.6246
2.6118 296.0 4144 7.5817
2.6894 297.0 4158 7.5868
2.5624 298.0 4172 7.5837
2.5449 299.0 4186 7.6007
2.5865 300.0 4200 7.6604
2.5366 301.0 4214 7.5909
2.4286 302.0 4228 7.6563
2.6909 303.0 4242 7.6767
2.4252 304.0 4256 7.6556
2.612 305.0 4270 7.6846
2.4793 306.0 4284 7.6279
2.5227 307.0 4298 7.6808
2.5756 308.0 4312 7.6703
2.5321 309.0 4326 7.6217
2.5568 310.0 4340 7.6381
2.507 311.0 4354 7.6528
2.5766 312.0 4368 7.6480
2.3532 313.0 4382 7.6255
2.4758 314.0 4396 7.6512
2.4304 315.0 4410 7.6606
2.4749 316.0 4424 7.6470
2.4886 317.0 4438 7.7193
2.511 318.0 4452 7.6670
2.4664 319.0 4466 7.6209
2.4981 320.0 4480 7.6819
2.4406 321.0 4494 7.6661
2.5787 322.0 4508 7.6903
2.4885 323.0 4522 7.6595
2.5796 324.0 4536 7.6882
2.4909 325.0 4550 7.7169
2.522 326.0 4564 7.6606
2.4206 327.0 4578 7.6526
2.4909 328.0 4592 7.6731
2.4543 329.0 4606 7.6822
2.4431 330.0 4620 7.6770
2.3963 331.0 4634 7.6407
2.4518 332.0 4648 7.6468
2.5734 333.0 4662 7.7206
2.4423 334.0 4676 7.6691
2.4418 335.0 4690 7.6822
2.4575 336.0 4704 7.6477
2.4671 337.0 4718 7.6888
2.3527 338.0 4732 7.7104
2.473 339.0 4746 7.7247
2.4786 340.0 4760 7.7340
2.4222 341.0 4774 7.6998
2.4812 342.0 4788 7.6996
2.3484 343.0 4802 7.6807
2.3231 344.0 4816 7.6972
2.4844 345.0 4830 7.6984
2.3757 346.0 4844 7.7091
2.4139 347.0 4858 7.7240
2.3665 348.0 4872 7.7681
2.3942 349.0 4886 7.7129
2.2922 350.0 4900 7.6804
2.4234 351.0 4914 7.7445
2.3589 352.0 4928 7.7599
2.3987 353.0 4942 7.7381
2.3545 354.0 4956 7.7433
2.4019 355.0 4970 7.7560
2.2925 356.0 4984 7.7393
2.3678 357.0 4998 7.7211
2.3588 358.0 5012 7.7414
2.3996 359.0 5026 7.7436
2.3665 360.0 5040 7.7966
2.3374 361.0 5054 7.8225
2.3667 362.0 5068 7.7955
2.3754 363.0 5082 7.7731
2.4179 364.0 5096 7.7899
2.3777 365.0 5110 7.7831
2.4064 366.0 5124 7.7861
2.3371 367.0 5138 7.7578
2.4169 368.0 5152 7.8429
2.3491 369.0 5166 7.7645
2.2275 370.0 5180 7.8063
2.2605 371.0 5194 7.8280
2.3506 372.0 5208 7.7356
2.403 373.0 5222 7.7739
2.3188 374.0 5236 7.7634
2.3294 375.0 5250 7.8033
2.2724 376.0 5264 7.8423
2.2704 377.0 5278 7.8340
2.2606 378.0 5292 7.7941
2.2599 379.0 5306 7.8336
2.326 380.0 5320 7.8080
2.2861 381.0 5334 7.8097
2.2559 382.0 5348 7.8201
2.2612 383.0 5362 7.8249
2.3161 384.0 5376 7.8353
2.2061 385.0 5390 7.8623
2.4231 386.0 5404 7.8568
2.2481 387.0 5418 7.8642
2.2319 388.0 5432 7.8255
2.2178 389.0 5446 7.8136
2.3153 390.0 5460 7.8549
2.2391 391.0 5474 7.8739
2.2736 392.0 5488 7.9016
2.3335 393.0 5502 7.8838
2.2069 394.0 5516 7.9268
2.303 395.0 5530 7.8096
2.2585 396.0 5544 7.8667
2.2261 397.0 5558 7.8651
2.2792 398.0 5572 7.8213
2.3172 399.0 5586 7.8702
2.2787 400.0 5600 7.8745
2.226 401.0 5614 7.8490
2.1491 402.0 5628 7.8608
2.2121 403.0 5642 7.8568
2.1715 404.0 5656 7.8996
2.1613 405.0 5670 7.8920
2.1886 406.0 5684 7.8223
2.1392 407.0 5698 7.8254
2.2268 408.0 5712 7.8583
2.2726 409.0 5726 7.8749
2.1648 410.0 5740 7.9115
2.1897 411.0 5754 7.9030
2.1597 412.0 5768 7.8699
2.1989 413.0 5782 7.8932
2.2705 414.0 5796 7.8936
2.1071 415.0 5810 7.8695
2.124 416.0 5824 7.8873
2.1948 417.0 5838 7.8655
2.2704 418.0 5852 7.9172
2.2055 419.0 5866 7.9646
2.276 420.0 5880 7.9224
2.1541 421.0 5894 7.8567
2.1881 422.0 5908 7.8945
2.1455 423.0 5922 7.8674
2.3452 424.0 5936 7.9724
2.1371 425.0 5950 7.9671
2.1901 426.0 5964 7.9274
2.1643 427.0 5978 7.9121
2.2229 428.0 5992 7.8934
2.1254 429.0 6006 7.9270
2.1554 430.0 6020 7.9205
2.0761 431.0 6034 7.9256
2.1551 432.0 6048 7.9133
2.2451 433.0 6062 7.9323
2.1491 434.0 6076 7.9551
2.1766 435.0 6090 7.9279
2.1239 436.0 6104 7.8983
2.1505 437.0 6118 7.9169
2.153 438.0 6132 7.9516
2.0899 439.0 6146 7.9140
2.1215 440.0 6160 7.9224
2.0644 441.0 6174 7.9485
2.1333 442.0 6188 7.9633
2.0807 443.0 6202 7.9847
2.1222 444.0 6216 7.9519
2.0775 445.0 6230 7.9995
2.1712 446.0 6244 7.9453
2.1816 447.0 6258 7.9563
2.071 448.0 6272 7.9443
2.083 449.0 6286 7.9434
2.166 450.0 6300 7.9449
2.1607 451.0 6314 7.9534
2.1057 452.0 6328 7.9520
2.1258 453.0 6342 7.9578
2.0822 454.0 6356 7.9709
2.0092 455.0 6370 8.0117
2.055 456.0 6384 7.9800
2.0325 457.0 6398 7.9150
2.0546 458.0 6412 7.9607
2.0677 459.0 6426 7.9714
2.1351 460.0 6440 7.9851
2.0859 461.0 6454 8.0055
2.0274 462.0 6468 7.9691
2.0006 463.0 6482 7.9561
2.1271 464.0 6496 7.9346
2.0637 465.0 6510 8.0015
2.0727 466.0 6524 8.0062
1.983 467.0 6538 8.0255
2.0895 468.0 6552 7.9777
2.1187 469.0 6566 7.9704
2.0874 470.0 6580 7.9550
2.0927 471.0 6594 7.9987
2.1442 472.0 6608 8.0421
2.0117 473.0 6622 8.0121
2.0647 474.0 6636 7.9565
2.0095 475.0 6650 7.9986
2.0008 476.0 6664 8.0411
2.0464 477.0 6678 7.9803
2.1314 478.0 6692 8.0383
2.0345 479.0 6706 7.9776
2.0668 480.0 6720 8.0702
2.0933 481.0 6734 8.0149
2.0612 482.0 6748 8.0105
1.9858 483.0 6762 7.9859
2.0195 484.0 6776 7.9764
2.0203 485.0 6790 8.0284
1.9986 486.0 6804 7.9929
2.0372 487.0 6818 7.9623
1.9485 488.0 6832 8.0172
1.9316 489.0 6846 7.9999
2.0008 490.0 6860 7.9783
2.0899 491.0 6874 8.0318
2.0078 492.0 6888 7.9986
2.0386 493.0 6902 8.0367
2.006 494.0 6916 8.0206
1.981 495.0 6930 8.0008
2.0464 496.0 6944 8.0056
1.9485 497.0 6958 8.0243
2.0409 498.0 6972 8.0541
2.0374 499.0 6986 8.0330
2.0073 500.0 7000 8.0471
2.0605 501.0 7014 8.0782
2.0424 502.0 7028 8.0568
2.0192 503.0 7042 8.0502
1.9831 504.0 7056 8.0580
2.1012 505.0 7070 8.0488
1.9765 506.0 7084 8.0293
2.0735 507.0 7098 8.0325
1.9964 508.0 7112 8.0104
1.9963 509.0 7126 8.0233
2.0252 510.0 7140 8.0312
1.9223 511.0 7154 8.0337
2.0063 512.0 7168 8.0609
2.0272 513.0 7182 8.0299
1.9498 514.0 7196 8.0298
2.0057 515.0 7210 8.0949
1.9598 516.0 7224 8.0999
1.949 517.0 7238 8.0914
2.0215 518.0 7252 8.0730
2.0068 519.0 7266 8.0657
1.9337 520.0 7280 8.0926
2.0259 521.0 7294 8.0900
1.9699 522.0 7308 8.0874
1.9511 523.0 7322 8.1374
1.8801 524.0 7336 8.0852
2.0123 525.0 7350 8.0754
1.9374 526.0 7364 8.0685
1.9303 527.0 7378 8.0832
1.963 528.0 7392 8.0756
1.9235 529.0 7406 8.1209
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1.6465 999.0 13986 8.5004
1.6321 1000.0 14000 8.4563

Framework versions

  • Transformers 4.13.0
  • Pytorch 1.12.0+cu113
  • Datasets 1.16.1
  • Tokenizers 0.10.3