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bert_baseline_prompt_adherence_task4_fold2

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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_task4_fold2
    results: []

bert_baseline_prompt_adherence_task4_fold2

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: 0.3619
  • Qwk: 0.6718
  • Mse: 0.3642

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 0.0299 2 1.6150 0.0 1.6151
No log 0.0597 4 1.1131 0.0 1.1127
No log 0.0896 6 0.9923 0.0 0.9917
No log 0.1194 8 0.8764 0.0931 0.8757
No log 0.1493 10 0.7878 0.3258 0.7870
No log 0.1791 12 0.7017 0.3282 0.7009
No log 0.2090 14 0.6637 0.3119 0.6629
No log 0.2388 16 0.6324 0.3554 0.6317
No log 0.2687 18 0.7643 0.2593 0.7637
No log 0.2985 20 0.6080 0.3281 0.6076
No log 0.3284 22 0.5178 0.3875 0.5177
No log 0.3582 24 0.5524 0.3591 0.5525
No log 0.3881 26 0.5475 0.3552 0.5478
No log 0.4179 28 0.4919 0.3781 0.4925
No log 0.4478 30 0.5056 0.3505 0.5060
No log 0.4776 32 0.5090 0.3430 0.5097
No log 0.5075 34 0.4966 0.4605 0.4976
No log 0.5373 36 0.5050 0.5425 0.5062
No log 0.5672 38 0.5247 0.6176 0.5262
No log 0.5970 40 0.5400 0.6151 0.5417
No log 0.6269 42 0.5638 0.5715 0.5656
No log 0.6567 44 0.5227 0.5910 0.5246
No log 0.6866 46 0.5162 0.6358 0.5182
No log 0.7164 48 0.5014 0.6362 0.5034
No log 0.7463 50 0.4957 0.6499 0.4976
No log 0.7761 52 0.4510 0.6120 0.4528
No log 0.8060 54 0.4435 0.4895 0.4450
No log 0.8358 56 0.4428 0.4449 0.4440
No log 0.8657 58 0.4246 0.5098 0.4260
No log 0.8955 60 0.4176 0.5447 0.4191
No log 0.9254 62 0.4144 0.5936 0.4160
No log 0.9552 64 0.4111 0.6017 0.4127
No log 0.9851 66 0.4215 0.5073 0.4229
No log 1.0149 68 0.4799 0.3889 0.4809
No log 1.0448 70 0.4582 0.4065 0.4593
No log 1.0746 72 0.3961 0.5408 0.3976
No log 1.1045 74 0.3860 0.5622 0.3876
No log 1.1343 76 0.3850 0.5397 0.3865
No log 1.1642 78 0.3971 0.4816 0.3985
No log 1.1940 80 0.4177 0.4745 0.4191
No log 1.2239 82 0.4110 0.5098 0.4126
No log 1.2537 84 0.3889 0.5834 0.3906
No log 1.2836 86 0.3825 0.6343 0.3843
No log 1.3134 88 0.3983 0.6735 0.4000
No log 1.3433 90 0.3892 0.6564 0.3910
No log 1.3731 92 0.4124 0.5726 0.4143
No log 1.4030 94 0.4329 0.5433 0.4347
No log 1.4328 96 0.3962 0.5530 0.3982
No log 1.4627 98 0.3875 0.5613 0.3895
No log 1.4925 100 0.3712 0.6099 0.3733
No log 1.5224 102 0.3695 0.6647 0.3719
No log 1.5522 104 0.3651 0.6477 0.3675
No log 1.5821 106 0.3638 0.6590 0.3662
No log 1.6119 108 0.3697 0.6664 0.3723
No log 1.6418 110 0.3732 0.6626 0.3759
No log 1.6716 112 0.3828 0.6856 0.3856
No log 1.7015 114 0.4137 0.7194 0.4164
No log 1.7313 116 0.3987 0.7078 0.4015
No log 1.7612 118 0.3763 0.6479 0.3790
No log 1.7910 120 0.4326 0.5145 0.4345
No log 1.8209 122 0.4430 0.4898 0.4446
No log 1.8507 124 0.3836 0.5850 0.3858
No log 1.8806 126 0.3662 0.6777 0.3690
No log 1.9104 128 0.3657 0.6847 0.3686
No log 1.9403 130 0.3716 0.6916 0.3745
No log 1.9701 132 0.3571 0.6809 0.3597
No log 2.0 134 0.3441 0.6243 0.3461
No log 2.0299 136 0.3643 0.5408 0.3658
No log 2.0597 138 0.3673 0.5518 0.3688
No log 2.0896 140 0.3785 0.5621 0.3801
No log 2.1194 142 0.3667 0.5927 0.3684
No log 2.1493 144 0.3548 0.6597 0.3568
No log 2.1791 146 0.3561 0.6778 0.3583
No log 2.2090 148 0.3534 0.6716 0.3554
No log 2.2388 150 0.3540 0.6743 0.3560
No log 2.2687 152 0.3537 0.6544 0.3555
No log 2.2985 154 0.3533 0.6431 0.3550
No log 2.3284 156 0.3628 0.6787 0.3651
No log 2.3582 158 0.3772 0.6896 0.3799
No log 2.3881 160 0.3757 0.6716 0.3785
No log 2.4179 162 0.3721 0.6471 0.3745
No log 2.4478 164 0.3928 0.5908 0.3947
No log 2.4776 166 0.3910 0.5933 0.3928
No log 2.5075 168 0.3730 0.6497 0.3753
No log 2.5373 170 0.3663 0.6622 0.3689
No log 2.5672 172 0.3630 0.6852 0.3658
No log 2.5970 174 0.3529 0.6644 0.3554
No log 2.6269 176 0.3522 0.6532 0.3543
No log 2.6567 178 0.3531 0.6474 0.3552
No log 2.6866 180 0.3544 0.6314 0.3565
No log 2.7164 182 0.3551 0.6349 0.3573
No log 2.7463 184 0.3573 0.6408 0.3595
No log 2.7761 186 0.3585 0.6419 0.3607
No log 2.8060 188 0.3552 0.6452 0.3574
No log 2.8358 190 0.3526 0.6438 0.3548
No log 2.8657 192 0.3496 0.6430 0.3517
No log 2.8955 194 0.3533 0.6347 0.3551
No log 2.9254 196 0.3628 0.6228 0.3645
No log 2.9552 198 0.3575 0.6505 0.3596
No log 2.9851 200 0.3609 0.6649 0.3632
No log 3.0149 202 0.3745 0.6968 0.3773
No log 3.0448 204 0.3948 0.7071 0.3979
No log 3.0746 206 0.4027 0.7042 0.4059
No log 3.1045 208 0.3964 0.7026 0.3994
No log 3.1343 210 0.3705 0.6951 0.3730
No log 3.1642 212 0.3664 0.6148 0.3682
No log 3.1940 214 0.3754 0.5845 0.3770
No log 3.2239 216 0.3698 0.5859 0.3713
No log 3.2537 218 0.3582 0.6089 0.3598
No log 3.2836 220 0.3515 0.6564 0.3534
No log 3.3134 222 0.3522 0.6775 0.3543
No log 3.3433 224 0.3535 0.6820 0.3556
No log 3.3731 226 0.3554 0.6878 0.3576
No log 3.4030 228 0.3605 0.6915 0.3630
No log 3.4328 230 0.3839 0.7020 0.3867
No log 3.4627 232 0.3961 0.7105 0.3990
No log 3.4925 234 0.3751 0.7051 0.3778
No log 3.5224 236 0.3457 0.6892 0.3479
No log 3.5522 238 0.3464 0.6424 0.3479
No log 3.5821 240 0.3583 0.6144 0.3597
No log 3.6119 242 0.3556 0.6319 0.3571
No log 3.6418 244 0.3514 0.6898 0.3534
No log 3.6716 246 0.3516 0.6929 0.3537
No log 3.7015 248 0.3512 0.6900 0.3533
No log 3.7313 250 0.3522 0.6904 0.3543
No log 3.7612 252 0.3510 0.6830 0.3530
No log 3.7910 254 0.3507 0.6780 0.3526
No log 3.8209 256 0.3612 0.6288 0.3626
No log 3.8507 258 0.3904 0.5419 0.3914
No log 3.8806 260 0.3907 0.5404 0.3917
No log 3.9104 262 0.3671 0.5869 0.3683
No log 3.9403 264 0.3493 0.6553 0.3510
No log 3.9701 266 0.3487 0.6782 0.3508
No log 4.0 268 0.3501 0.6847 0.3523
No log 4.0299 270 0.3476 0.6695 0.3497
No log 4.0597 272 0.3472 0.6652 0.3490
No log 4.0896 274 0.3531 0.6503 0.3548
No log 4.1194 276 0.3593 0.6312 0.3610
No log 4.1493 278 0.3624 0.6358 0.3641
No log 4.1791 280 0.3685 0.6320 0.3703
No log 4.2090 282 0.3659 0.6432 0.3678
No log 4.2388 284 0.3634 0.6778 0.3657
No log 4.2687 286 0.3687 0.6865 0.3713
No log 4.2985 288 0.3752 0.6901 0.3780
No log 4.3284 290 0.3746 0.6925 0.3774
No log 4.3582 292 0.3677 0.6883 0.3702
No log 4.3881 294 0.3627 0.6674 0.3649
No log 4.4179 296 0.3664 0.6362 0.3683
No log 4.4478 298 0.3710 0.6230 0.3727
No log 4.4776 300 0.3702 0.6190 0.3719
No log 4.5075 302 0.3687 0.6266 0.3704
No log 4.5373 304 0.3642 0.6383 0.3660
No log 4.5672 306 0.3607 0.6552 0.3626
No log 4.5970 308 0.3603 0.6705 0.3625
No log 4.6269 310 0.3622 0.6824 0.3646
No log 4.6567 312 0.3636 0.6819 0.3660
No log 4.6866 314 0.3626 0.6819 0.3650
No log 4.7164 316 0.3613 0.6799 0.3636
No log 4.7463 318 0.3606 0.6772 0.3629
No log 4.7761 320 0.3605 0.6736 0.3627
No log 4.8060 322 0.3607 0.6665 0.3629
No log 4.8358 324 0.3607 0.6611 0.3629
No log 4.8657 326 0.3609 0.6727 0.3630
No log 4.8955 328 0.3611 0.6736 0.3633
No log 4.9254 330 0.3615 0.6698 0.3638
No log 4.9552 332 0.3618 0.6718 0.3641
No log 4.9851 334 0.3619 0.6718 0.3642

Framework versions

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