--- license: apache-2.0 base_model: google-bert/bert-base-cased tags: - generated_from_trainer model-index: - name: bert_baseline_prompt_adherence_task3_fold2 results: [] --- # bert_baseline_prompt_adherence_task3_fold2 This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3865 - Qwk: 0.6205 - Mse: 0.3868 ## 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 | 0.0308 | 2 | 0.9209 | 0.0721 | 0.9218 | | No log | 0.0615 | 4 | 0.7058 | 0.0 | 0.7068 | | No log | 0.0923 | 6 | 0.6332 | 0.0 | 0.6344 | | No log | 0.1231 | 8 | 0.6461 | 0.0 | 0.6473 | | No log | 0.1538 | 10 | 0.6356 | 0.0 | 0.6368 | | No log | 0.1846 | 12 | 0.5833 | 0.0 | 0.5844 | | No log | 0.2154 | 14 | 0.5584 | 0.0 | 0.5595 | | No log | 0.2462 | 16 | 0.5636 | 0.0 | 0.5645 | | No log | 0.2769 | 18 | 0.5578 | 0.0 | 0.5588 | | No log | 0.3077 | 20 | 0.5330 | 0.0090 | 0.5340 | | No log | 0.3385 | 22 | 0.4862 | 0.0297 | 0.4871 | | No log | 0.3692 | 24 | 0.4627 | 0.1885 | 0.4635 | | No log | 0.4 | 26 | 0.4589 | 0.4569 | 0.4597 | | No log | 0.4308 | 28 | 0.4252 | 0.5118 | 0.4259 | | No log | 0.4615 | 30 | 0.4208 | 0.5424 | 0.4214 | | No log | 0.4923 | 32 | 0.4120 | 0.4962 | 0.4126 | | No log | 0.5231 | 34 | 0.4650 | 0.3983 | 0.4657 | | No log | 0.5538 | 36 | 0.6042 | 0.2581 | 0.6049 | | No log | 0.5846 | 38 | 0.5797 | 0.2927 | 0.5804 | | No log | 0.6154 | 40 | 0.4671 | 0.3941 | 0.4677 | | No log | 0.6462 | 42 | 0.4642 | 0.4488 | 0.4647 | | No log | 0.6769 | 44 | 0.4843 | 0.5479 | 0.4848 | | No log | 0.7077 | 46 | 0.4777 | 0.6022 | 0.4781 | | No log | 0.7385 | 48 | 0.4644 | 0.5947 | 0.4648 | | No log | 0.7692 | 50 | 0.3865 | 0.5476 | 0.3870 | | No log | 0.8 | 52 | 0.3739 | 0.5548 | 0.3743 | | No log | 0.8308 | 54 | 0.4036 | 0.6030 | 0.4040 | | No log | 0.8615 | 56 | 0.4922 | 0.6210 | 0.4926 | | No log | 0.8923 | 58 | 0.5134 | 0.6215 | 0.5138 | | No log | 0.9231 | 60 | 0.4476 | 0.6219 | 0.4479 | | No log | 0.9538 | 62 | 0.4020 | 0.6279 | 0.4023 | | No log | 0.9846 | 64 | 0.3963 | 0.6294 | 0.3966 | | No log | 1.0154 | 66 | 0.3739 | 0.6026 | 0.3742 | | No log | 1.0462 | 68 | 0.3901 | 0.6210 | 0.3903 | | No log | 1.0769 | 70 | 0.3873 | 0.6134 | 0.3875 | | No log | 1.1077 | 72 | 0.4214 | 0.6277 | 0.4215 | | No log | 1.1385 | 74 | 0.4557 | 0.6312 | 0.4558 | | No log | 1.1692 | 76 | 0.4140 | 0.6287 | 0.4141 | | No log | 1.2 | 78 | 0.3723 | 0.5992 | 0.3725 | | No log | 1.2308 | 80 | 0.3738 | 0.5884 | 0.3740 | | No log | 1.2615 | 82 | 0.3897 | 0.6109 | 0.3898 | | No log | 1.2923 | 84 | 0.4131 | 0.6202 | 0.4132 | | No log | 1.3231 | 86 | 0.4389 | 0.6198 | 0.4391 | | No log | 1.3538 | 88 | 0.4140 | 0.6212 | 0.4142 | | No log | 1.3846 | 90 | 0.3720 | 0.6116 | 0.3723 | | No log | 1.4154 | 92 | 0.3373 | 0.5762 | 0.3376 | | No log | 1.4462 | 94 | 0.3269 | 0.5504 | 0.3273 | | No log | 1.4769 | 96 | 0.3340 | 0.6284 | 0.3344 | | No log | 1.5077 | 98 | 0.3765 | 0.6424 | 0.3769 | | No log | 1.5385 | 100 | 0.4626 | 0.6258 | 0.4631 | | No log | 1.5692 | 102 | 0.4455 | 0.6303 | 0.4461 | | No log | 1.6 | 104 | 0.3552 | 0.6401 | 0.3558 | | No log | 1.6308 | 106 | 0.3091 | 0.5522 | 0.3097 | | No log | 1.6615 | 108 | 0.3105 | 0.5415 | 0.3111 | | No log | 1.6923 | 110 | 0.3240 | 0.6195 | 0.3247 | | No log | 1.7231 | 112 | 0.3762 | 0.6409 | 0.3770 | | No log | 1.7538 | 114 | 0.4521 | 0.6156 | 0.4529 | | No log | 1.7846 | 116 | 0.4163 | 0.6405 | 0.4170 | | No log | 1.8154 | 118 | 0.3626 | 0.6411 | 0.3633 | | No log | 1.8462 | 120 | 0.3529 | 0.6359 | 0.3536 | | No log | 1.8769 | 122 | 0.3726 | 0.6447 | 0.3734 | | No log | 1.9077 | 124 | 0.3840 | 0.6250 | 0.3847 | | No log | 1.9385 | 126 | 0.3554 | 0.6208 | 0.3562 | | No log | 1.9692 | 128 | 0.3276 | 0.5576 | 0.3285 | | No log | 2.0 | 130 | 0.3269 | 0.5270 | 0.3278 | | No log | 2.0308 | 132 | 0.3320 | 0.5808 | 0.3328 | | No log | 2.0615 | 134 | 0.3699 | 0.6345 | 0.3706 | | No log | 2.0923 | 136 | 0.3914 | 0.6391 | 0.3919 | | No log | 2.1231 | 138 | 0.3926 | 0.6470 | 0.3932 | | No log | 2.1538 | 140 | 0.3570 | 0.6304 | 0.3574 | | No log | 2.1846 | 142 | 0.3445 | 0.5527 | 0.3449 | | No log | 2.2154 | 144 | 0.3578 | 0.5157 | 0.3582 | | No log | 2.2462 | 146 | 0.3503 | 0.5666 | 0.3506 | | No log | 2.2769 | 148 | 0.4131 | 0.6374 | 0.4133 | | No log | 2.3077 | 150 | 0.5248 | 0.6554 | 0.5249 | | No log | 2.3385 | 152 | 0.5552 | 0.6448 | 0.5553 | | No log | 2.3692 | 154 | 0.4859 | 0.6509 | 0.4861 | | No log | 2.4 | 156 | 0.3954 | 0.6432 | 0.3956 | | No log | 2.4308 | 158 | 0.3557 | 0.6127 | 0.3560 | | No log | 2.4615 | 160 | 0.3583 | 0.6304 | 0.3585 | | No log | 2.4923 | 162 | 0.3558 | 0.6184 | 0.3560 | | No log | 2.5231 | 164 | 0.3630 | 0.6348 | 0.3632 | | No log | 2.5538 | 166 | 0.3875 | 0.6517 | 0.3877 | | No log | 2.5846 | 168 | 0.3741 | 0.6488 | 0.3743 | | No log | 2.6154 | 170 | 0.3590 | 0.6356 | 0.3593 | | No log | 2.6462 | 172 | 0.3372 | 0.5962 | 0.3375 | | No log | 2.6769 | 174 | 0.3386 | 0.6013 | 0.3388 | | No log | 2.7077 | 176 | 0.3585 | 0.6326 | 0.3587 | | No log | 2.7385 | 178 | 0.3830 | 0.6366 | 0.3832 | | No log | 2.7692 | 180 | 0.3715 | 0.6394 | 0.3717 | | No log | 2.8 | 182 | 0.3562 | 0.6129 | 0.3564 | | No log | 2.8308 | 184 | 0.3686 | 0.6059 | 0.3687 | | No log | 2.8615 | 186 | 0.4020 | 0.6375 | 0.4021 | | No log | 2.8923 | 188 | 0.4058 | 0.6248 | 0.4058 | | No log | 2.9231 | 190 | 0.3896 | 0.6170 | 0.3897 | | No log | 2.9538 | 192 | 0.3750 | 0.6119 | 0.3752 | | No log | 2.9846 | 194 | 0.3567 | 0.5864 | 0.3570 | | No log | 3.0154 | 196 | 0.3520 | 0.5827 | 0.3523 | | No log | 3.0462 | 198 | 0.3761 | 0.6138 | 0.3763 | | No log | 3.0769 | 200 | 0.4113 | 0.6249 | 0.4115 | | No log | 3.1077 | 202 | 0.4565 | 0.6324 | 0.4567 | | No log | 3.1385 | 204 | 0.4397 | 0.6308 | 0.4398 | | No log | 3.1692 | 206 | 0.4039 | 0.6298 | 0.4041 | | No log | 3.2 | 208 | 0.3731 | 0.6179 | 0.3733 | | No log | 3.2308 | 210 | 0.3707 | 0.6174 | 0.3709 | | No log | 3.2615 | 212 | 0.3995 | 0.6206 | 0.3996 | | No log | 3.2923 | 214 | 0.4179 | 0.6259 | 0.4181 | | No log | 3.3231 | 216 | 0.4157 | 0.6315 | 0.4159 | | No log | 3.3538 | 218 | 0.4204 | 0.6264 | 0.4205 | | No log | 3.3846 | 220 | 0.3934 | 0.6247 | 0.3936 | | No log | 3.4154 | 222 | 0.3840 | 0.6296 | 0.3842 | | No log | 3.4462 | 224 | 0.3688 | 0.6245 | 0.3690 | | No log | 3.4769 | 226 | 0.3566 | 0.6139 | 0.3568 | | No log | 3.5077 | 228 | 0.3496 | 0.6088 | 0.3499 | | No log | 3.5385 | 230 | 0.3631 | 0.6246 | 0.3633 | | No log | 3.5692 | 232 | 0.3979 | 0.6243 | 0.3982 | | No log | 3.6 | 234 | 0.4009 | 0.6244 | 0.4011 | | No log | 3.6308 | 236 | 0.3887 | 0.6232 | 0.3889 | | No log | 3.6615 | 238 | 0.3761 | 0.6199 | 0.3764 | | No log | 3.6923 | 240 | 0.3744 | 0.6173 | 0.3747 | | No log | 3.7231 | 242 | 0.3733 | 0.6157 | 0.3736 | | No log | 3.7538 | 244 | 0.3747 | 0.6199 | 0.3749 | | No log | 3.7846 | 246 | 0.3837 | 0.6211 | 0.3839 | | No log | 3.8154 | 248 | 0.3847 | 0.6274 | 0.3850 | | No log | 3.8462 | 250 | 0.3831 | 0.6205 | 0.3834 | | No log | 3.8769 | 252 | 0.3816 | 0.6199 | 0.3819 | | No log | 3.9077 | 254 | 0.3958 | 0.6242 | 0.3961 | | No log | 3.9385 | 256 | 0.3982 | 0.6242 | 0.3985 | | No log | 3.9692 | 258 | 0.4001 | 0.6200 | 0.4004 | | No log | 4.0 | 260 | 0.4020 | 0.6152 | 0.4022 | | No log | 4.0308 | 262 | 0.4158 | 0.6227 | 0.4160 | | No log | 4.0615 | 264 | 0.4118 | 0.6227 | 0.4121 | | No log | 4.0923 | 266 | 0.4022 | 0.6173 | 0.4025 | | No log | 4.1231 | 268 | 0.4025 | 0.6184 | 0.4028 | | No log | 4.1538 | 270 | 0.4206 | 0.6190 | 0.4208 | | No log | 4.1846 | 272 | 0.4420 | 0.6309 | 0.4422 | | No log | 4.2154 | 274 | 0.4818 | 0.6453 | 0.4820 | | No log | 4.2462 | 276 | 0.4957 | 0.6506 | 0.4959 | | No log | 4.2769 | 278 | 0.4752 | 0.6434 | 0.4754 | | No log | 4.3077 | 280 | 0.4413 | 0.6298 | 0.4416 | | No log | 4.3385 | 282 | 0.4079 | 0.6117 | 0.4082 | | No log | 4.3692 | 284 | 0.3895 | 0.6052 | 0.3898 | | No log | 4.4 | 286 | 0.3731 | 0.6013 | 0.3734 | | No log | 4.4308 | 288 | 0.3693 | 0.5932 | 0.3697 | | No log | 4.4615 | 290 | 0.3701 | 0.5952 | 0.3705 | | No log | 4.4923 | 292 | 0.3759 | 0.6067 | 0.3763 | | No log | 4.5231 | 294 | 0.3872 | 0.6169 | 0.3875 | | No log | 4.5538 | 296 | 0.4009 | 0.6131 | 0.4012 | | No log | 4.5846 | 298 | 0.4136 | 0.6120 | 0.4139 | | No log | 4.6154 | 300 | 0.4345 | 0.6288 | 0.4348 | | No log | 4.6462 | 302 | 0.4442 | 0.6402 | 0.4445 | | No log | 4.6769 | 304 | 0.4404 | 0.6380 | 0.4407 | | No log | 4.7077 | 306 | 0.4287 | 0.6233 | 0.4291 | | No log | 4.7385 | 308 | 0.4234 | 0.6184 | 0.4237 | | No log | 4.7692 | 310 | 0.4168 | 0.6205 | 0.4171 | | No log | 4.8 | 312 | 0.4091 | 0.6173 | 0.4095 | | No log | 4.8308 | 314 | 0.4006 | 0.6179 | 0.4009 | | No log | 4.8615 | 316 | 0.3935 | 0.6189 | 0.3938 | | No log | 4.8923 | 318 | 0.3890 | 0.6189 | 0.3894 | | No log | 4.9231 | 320 | 0.3871 | 0.6142 | 0.3875 | | No log | 4.9538 | 322 | 0.3868 | 0.6142 | 0.3872 | | No log | 4.9846 | 324 | 0.3865 | 0.6205 | 0.3868 | ### Framework versions - Transformers 4.42.3 - Pytorch 2.1.2 - Datasets 2.20.0 - Tokenizers 0.19.1