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bert_baseline_prompt_adherence_task6_fold3

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metadata
license: apache-2.0
base_model: google-bert/bert-base-cased
tags:
  - generated_from_trainer
model-index:
  - name: bert_baseline_prompt_adherence_task6_fold3
    results: []

bert_baseline_prompt_adherence_task6_fold3

This model is a fine-tuned version of google-bert/bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4247
  • Qwk: 0.7754
  • Mse: 0.4247

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Qwk Mse
No log 0.0294 2 1.7612 0.0 1.7612
No log 0.0588 4 1.4976 -0.0486 1.4976
No log 0.0882 6 1.3256 -0.0045 1.3256
No log 0.1176 8 1.0956 0.0 1.0956
No log 0.1471 10 0.9927 0.0 0.9927
No log 0.1765 12 0.9586 0.0 0.9586
No log 0.2059 14 0.8770 0.0 0.8770
No log 0.2353 16 0.8268 0.2233 0.8268
No log 0.2647 18 0.7869 0.4102 0.7869
No log 0.2941 20 0.7539 0.4667 0.7539
No log 0.3235 22 0.6848 0.4524 0.6848
No log 0.3529 24 0.6251 0.3985 0.6251
No log 0.3824 26 0.5728 0.4507 0.5728
No log 0.4118 28 0.5804 0.5026 0.5804
No log 0.4412 30 0.6041 0.4997 0.6041
No log 0.4706 32 0.4732 0.4918 0.4732
No log 0.5 34 0.4584 0.5333 0.4584
No log 0.5294 36 0.5895 0.5679 0.5895
No log 0.5588 38 0.5094 0.6123 0.5094
No log 0.5882 40 0.5028 0.6302 0.5028
No log 0.6176 42 0.4369 0.6373 0.4369
No log 0.6471 44 0.4934 0.4785 0.4934
No log 0.6765 46 0.5004 0.4726 0.5004
No log 0.7059 48 0.4262 0.7031 0.4262
No log 0.7353 50 0.5825 0.6763 0.5825
No log 0.7647 52 0.4681 0.6710 0.4681
No log 0.7941 54 0.3762 0.6538 0.3762
No log 0.8235 56 0.3737 0.6383 0.3737
No log 0.8529 58 0.3822 0.6748 0.3822
No log 0.8824 60 0.3905 0.6817 0.3905
No log 0.9118 62 0.3853 0.6730 0.3853
No log 0.9412 64 0.3845 0.6766 0.3845
No log 0.9706 66 0.3865 0.6717 0.3865
No log 1.0 68 0.4478 0.6696 0.4478
No log 1.0294 70 0.5322 0.6747 0.5322
No log 1.0588 72 0.4563 0.6951 0.4563
No log 1.0882 74 0.4128 0.6789 0.4128
No log 1.1176 76 0.4267 0.7117 0.4267
No log 1.1471 78 0.5439 0.7687 0.5439
No log 1.1765 80 0.5451 0.7671 0.5451
No log 1.2059 82 0.3950 0.6714 0.3950
No log 1.2353 84 0.3919 0.5799 0.3919
No log 1.2647 86 0.4102 0.5500 0.4102
No log 1.2941 88 0.3534 0.6453 0.3534
No log 1.3235 90 0.4337 0.6800 0.4337
No log 1.3529 92 0.5133 0.6574 0.5133
No log 1.3824 94 0.4936 0.6765 0.4936
No log 1.4118 96 0.3690 0.6859 0.3690
No log 1.4412 98 0.3403 0.6334 0.3403
No log 1.4706 100 0.3431 0.6301 0.3431
No log 1.5 102 0.3333 0.6502 0.3333
No log 1.5294 104 0.4377 0.7022 0.4377
No log 1.5588 106 0.5763 0.7012 0.5763
No log 1.5882 108 0.5293 0.6672 0.5293
No log 1.6176 110 0.4315 0.6747 0.4315
No log 1.6471 112 0.3583 0.6808 0.3583
No log 1.6765 114 0.3511 0.6735 0.3511
No log 1.7059 116 0.3478 0.6618 0.3478
No log 1.7353 118 0.3474 0.6507 0.3474
No log 1.7647 120 0.3620 0.6630 0.3620
No log 1.7941 122 0.3894 0.6804 0.3894
No log 1.8235 124 0.4057 0.6852 0.4057
No log 1.8529 126 0.4497 0.6764 0.4497
No log 1.8824 128 0.3986 0.6851 0.3986
No log 1.9118 130 0.3293 0.6466 0.3293
No log 1.9412 132 0.3306 0.6285 0.3306
No log 1.9706 134 0.3381 0.6239 0.3381
No log 2.0 136 0.3413 0.6706 0.3413
No log 2.0294 138 0.4640 0.7789 0.4640
No log 2.0588 140 0.5489 0.7778 0.5489
No log 2.0882 142 0.4773 0.7819 0.4773
No log 2.1176 144 0.3711 0.7206 0.3711
No log 2.1471 146 0.3393 0.6336 0.3393
No log 2.1765 148 0.3465 0.6045 0.3465
No log 2.2059 150 0.3300 0.6413 0.3300
No log 2.2353 152 0.3591 0.7270 0.3591
No log 2.2647 154 0.4846 0.7874 0.4846
No log 2.2941 156 0.4862 0.7887 0.4862
No log 2.3235 158 0.3858 0.7422 0.3858
No log 2.3529 160 0.3396 0.6951 0.3396
No log 2.3824 162 0.3593 0.7225 0.3593
No log 2.4118 164 0.4085 0.7388 0.4085
No log 2.4412 166 0.4379 0.7507 0.4379
No log 2.4706 168 0.3953 0.7282 0.3953
No log 2.5 170 0.3341 0.6774 0.3341
No log 2.5294 172 0.3235 0.6494 0.3235
No log 2.5588 174 0.3218 0.6610 0.3218
No log 2.5882 176 0.3445 0.6891 0.3445
No log 2.6176 178 0.4174 0.7484 0.4174
No log 2.6471 180 0.4074 0.7478 0.4074
No log 2.6765 182 0.3458 0.7047 0.3458
No log 2.7059 184 0.3242 0.6716 0.3242
No log 2.7353 186 0.3304 0.6942 0.3304
No log 2.7647 188 0.3594 0.7320 0.3594
No log 2.7941 190 0.4304 0.7863 0.4304
No log 2.8235 192 0.4484 0.7965 0.4484
No log 2.8529 194 0.4058 0.7579 0.4058
No log 2.8824 196 0.3506 0.7108 0.3506
No log 2.9118 198 0.3382 0.7120 0.3382
No log 2.9412 200 0.3547 0.7253 0.3547
No log 2.9706 202 0.3676 0.7164 0.3676
No log 3.0 204 0.3491 0.6914 0.3491
No log 3.0294 206 0.3292 0.6816 0.3292
No log 3.0588 208 0.3223 0.6803 0.3223
No log 3.0882 210 0.3258 0.6989 0.3258
No log 3.1176 212 0.3207 0.7000 0.3207
No log 3.1471 214 0.3364 0.7168 0.3364
No log 3.1765 216 0.3697 0.7496 0.3697
No log 3.2059 218 0.3810 0.7657 0.3810
No log 3.2353 220 0.3702 0.7464 0.3702
No log 3.2647 222 0.3315 0.7005 0.3315
No log 3.2941 224 0.3241 0.6858 0.3241
No log 3.3235 226 0.3280 0.7003 0.3280
No log 3.3529 228 0.3536 0.7327 0.3536
No log 3.3824 230 0.4122 0.7663 0.4122
No log 3.4118 232 0.4680 0.7739 0.4680
No log 3.4412 234 0.4622 0.7703 0.4622
No log 3.4706 236 0.4020 0.7561 0.4020
No log 3.5 238 0.3521 0.7217 0.3521
No log 3.5294 240 0.3329 0.6738 0.3329
No log 3.5588 242 0.3358 0.6592 0.3358
No log 3.5882 244 0.3324 0.6681 0.3324
No log 3.6176 246 0.3434 0.7028 0.3434
No log 3.6471 248 0.3973 0.7504 0.3973
No log 3.6765 250 0.4777 0.7722 0.4777
No log 3.7059 252 0.4898 0.7732 0.4898
No log 3.7353 254 0.4411 0.7658 0.4411
No log 3.7647 256 0.3781 0.7255 0.3781
No log 3.7941 258 0.3491 0.7067 0.3491
No log 3.8235 260 0.3422 0.6995 0.3422
No log 3.8529 262 0.3415 0.7015 0.3415
No log 3.8824 264 0.3556 0.7104 0.3556
No log 3.9118 266 0.3833 0.7329 0.3833
No log 3.9412 268 0.3956 0.7442 0.3956
No log 3.9706 270 0.4082 0.7507 0.4082
No log 4.0 272 0.3878 0.7382 0.3878
No log 4.0294 274 0.3873 0.7374 0.3873
No log 4.0588 276 0.3782 0.7269 0.3782
No log 4.0882 278 0.3771 0.7269 0.3771
No log 4.1176 280 0.3708 0.7163 0.3708
No log 4.1471 282 0.3562 0.7133 0.3562
No log 4.1765 284 0.3492 0.7124 0.3492
No log 4.2059 286 0.3499 0.7111 0.3499
No log 4.2353 288 0.3450 0.7103 0.3450
No log 4.2647 290 0.3460 0.7077 0.3460
No log 4.2941 292 0.3568 0.7159 0.3568
No log 4.3235 294 0.3590 0.7237 0.3590
No log 4.3529 296 0.3593 0.7223 0.3593
No log 4.3824 298 0.3624 0.7269 0.3624
No log 4.4118 300 0.3731 0.7336 0.3731
No log 4.4412 302 0.3683 0.7301 0.3683
No log 4.4706 304 0.3664 0.7280 0.3664
No log 4.5 306 0.3577 0.7293 0.3577
No log 4.5294 308 0.3529 0.7255 0.3529
No log 4.5588 310 0.3467 0.7179 0.3467
No log 4.5882 312 0.3452 0.7054 0.3452
No log 4.6176 314 0.3451 0.7113 0.3451
No log 4.6471 316 0.3514 0.7212 0.3514
No log 4.6765 318 0.3596 0.7266 0.3596
No log 4.7059 320 0.3735 0.7376 0.3735
No log 4.7353 322 0.3884 0.7521 0.3884
No log 4.7647 324 0.4072 0.7658 0.4072
No log 4.7941 326 0.4235 0.7725 0.4235
No log 4.8235 328 0.4324 0.7807 0.4324
No log 4.8529 330 0.4356 0.7817 0.4356
No log 4.8824 332 0.4360 0.7801 0.4360
No log 4.9118 334 0.4343 0.7810 0.4343
No log 4.9412 336 0.4306 0.7823 0.4306
No log 4.9706 338 0.4266 0.7785 0.4266
No log 5.0 340 0.4247 0.7754 0.4247

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.1.2
  • Datasets 2.20.0
  • Tokenizers 0.19.1