--- license: apache-2.0 base_model: google-bert/bert-base-cased tags: - generated_from_trainer model-index: - name: bert_baseline_prompt_adherence_task3_fold0 results: [] --- # bert_baseline_prompt_adherence_task3_fold0 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: 0.2935 - Qwk: 0.6969 - Mse: 0.2933 ## 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 | 1.4854 | 0.0 | 1.4830 | | No log | 0.0615 | 4 | 1.1545 | 0.0 | 1.1527 | | No log | 0.0923 | 6 | 1.0353 | 0.1047 | 1.0337 | | No log | 0.1231 | 8 | 0.8265 | 0.0080 | 0.8256 | | No log | 0.1538 | 10 | 0.7134 | 0.0080 | 0.7131 | | No log | 0.1846 | 12 | 0.7006 | 0.0080 | 0.7006 | | No log | 0.2154 | 14 | 0.6698 | 0.0160 | 0.6697 | | No log | 0.2462 | 16 | 0.6591 | 0.0261 | 0.6587 | | No log | 0.2769 | 18 | 0.6070 | 0.0608 | 0.6065 | | No log | 0.3077 | 20 | 0.5114 | 0.3209 | 0.5113 | | No log | 0.3385 | 22 | 0.5089 | 0.5441 | 0.5090 | | No log | 0.3692 | 24 | 0.4664 | 0.5828 | 0.4664 | | No log | 0.4 | 26 | 0.4133 | 0.5528 | 0.4130 | | No log | 0.4308 | 28 | 0.3954 | 0.5784 | 0.3950 | | No log | 0.4615 | 30 | 0.4077 | 0.4964 | 0.4068 | | No log | 0.4923 | 32 | 0.4400 | 0.4461 | 0.4389 | | No log | 0.5231 | 34 | 0.3693 | 0.5871 | 0.3685 | | No log | 0.5538 | 36 | 0.4165 | 0.6417 | 0.4162 | | No log | 0.5846 | 38 | 0.4393 | 0.6482 | 0.4390 | | No log | 0.6154 | 40 | 0.3674 | 0.6179 | 0.3668 | | No log | 0.6462 | 42 | 0.4456 | 0.3881 | 0.4447 | | No log | 0.6769 | 44 | 0.5274 | 0.3133 | 0.5263 | | No log | 0.7077 | 46 | 0.4872 | 0.3225 | 0.4863 | | No log | 0.7385 | 48 | 0.4269 | 0.3624 | 0.4263 | | No log | 0.7692 | 50 | 0.4285 | 0.4215 | 0.4281 | | No log | 0.8 | 52 | 0.4577 | 0.6590 | 0.4574 | | No log | 0.8308 | 54 | 0.4957 | 0.6612 | 0.4955 | | No log | 0.8615 | 56 | 0.4681 | 0.6717 | 0.4679 | | No log | 0.8923 | 58 | 0.3478 | 0.6613 | 0.3475 | | No log | 0.9231 | 60 | 0.3521 | 0.5242 | 0.3515 | | No log | 0.9538 | 62 | 0.4063 | 0.4490 | 0.4055 | | No log | 0.9846 | 64 | 0.3644 | 0.5015 | 0.3637 | | No log | 1.0154 | 66 | 0.3224 | 0.6241 | 0.3220 | | No log | 1.0462 | 68 | 0.3547 | 0.6701 | 0.3545 | | No log | 1.0769 | 70 | 0.3713 | 0.6762 | 0.3711 | | No log | 1.1077 | 72 | 0.3302 | 0.6574 | 0.3299 | | No log | 1.1385 | 74 | 0.3111 | 0.6304 | 0.3107 | | No log | 1.1692 | 76 | 0.3082 | 0.6457 | 0.3078 | | No log | 1.2 | 78 | 0.3058 | 0.6367 | 0.3054 | | No log | 1.2308 | 80 | 0.3031 | 0.6176 | 0.3026 | | No log | 1.2615 | 82 | 0.3044 | 0.6173 | 0.3039 | | No log | 1.2923 | 84 | 0.2976 | 0.6220 | 0.2971 | | No log | 1.3231 | 86 | 0.3050 | 0.6457 | 0.3047 | | No log | 1.3538 | 88 | 0.3121 | 0.6704 | 0.3118 | | No log | 1.3846 | 90 | 0.2957 | 0.6403 | 0.2953 | | No log | 1.4154 | 92 | 0.2961 | 0.6064 | 0.2957 | | No log | 1.4462 | 94 | 0.2995 | 0.5934 | 0.2991 | | No log | 1.4769 | 96 | 0.2915 | 0.6499 | 0.2912 | | No log | 1.5077 | 98 | 0.3321 | 0.6978 | 0.3319 | | No log | 1.5385 | 100 | 0.4077 | 0.7087 | 0.4078 | | No log | 1.5692 | 102 | 0.3793 | 0.7102 | 0.3793 | | No log | 1.6 | 104 | 0.3049 | 0.6918 | 0.3048 | | No log | 1.6308 | 106 | 0.2953 | 0.6376 | 0.2950 | | No log | 1.6615 | 108 | 0.3054 | 0.6513 | 0.3052 | | No log | 1.6923 | 110 | 0.3162 | 0.6674 | 0.3160 | | No log | 1.7231 | 112 | 0.3023 | 0.6294 | 0.3020 | | No log | 1.7538 | 114 | 0.3041 | 0.6641 | 0.3038 | | No log | 1.7846 | 116 | 0.3123 | 0.6912 | 0.3120 | | No log | 1.8154 | 118 | 0.3106 | 0.6878 | 0.3103 | | No log | 1.8462 | 120 | 0.3049 | 0.6864 | 0.3046 | | No log | 1.8769 | 122 | 0.3027 | 0.6772 | 0.3024 | | No log | 1.9077 | 124 | 0.2932 | 0.6741 | 0.2928 | | No log | 1.9385 | 126 | 0.3010 | 0.6824 | 0.3006 | | No log | 1.9692 | 128 | 0.3298 | 0.6837 | 0.3295 | | No log | 2.0 | 130 | 0.3293 | 0.6857 | 0.3290 | | No log | 2.0308 | 132 | 0.3017 | 0.6529 | 0.3013 | | No log | 2.0615 | 134 | 0.3023 | 0.5797 | 0.3017 | | No log | 2.0923 | 136 | 0.3035 | 0.5761 | 0.3029 | | No log | 2.1231 | 138 | 0.2916 | 0.6173 | 0.2912 | | No log | 2.1538 | 140 | 0.3012 | 0.6787 | 0.3009 | | No log | 2.1846 | 142 | 0.2960 | 0.6767 | 0.2957 | | No log | 2.2154 | 144 | 0.2858 | 0.6631 | 0.2855 | | No log | 2.2462 | 146 | 0.2807 | 0.6614 | 0.2804 | | No log | 2.2769 | 148 | 0.2860 | 0.6577 | 0.2857 | | No log | 2.3077 | 150 | 0.2929 | 0.6777 | 0.2927 | | No log | 2.3385 | 152 | 0.2800 | 0.6558 | 0.2797 | | No log | 2.3692 | 154 | 0.2830 | 0.6594 | 0.2828 | | No log | 2.4 | 156 | 0.2810 | 0.6588 | 0.2808 | | No log | 2.4308 | 158 | 0.2975 | 0.6841 | 0.2974 | | No log | 2.4615 | 160 | 0.3103 | 0.6994 | 0.3102 | | No log | 2.4923 | 162 | 0.2931 | 0.6883 | 0.2930 | | No log | 2.5231 | 164 | 0.2755 | 0.6602 | 0.2753 | | No log | 2.5538 | 166 | 0.2733 | 0.6434 | 0.2731 | | No log | 2.5846 | 168 | 0.2833 | 0.6803 | 0.2831 | | No log | 2.6154 | 170 | 0.3004 | 0.7083 | 0.3003 | | No log | 2.6462 | 172 | 0.3652 | 0.7356 | 0.3652 | | No log | 2.6769 | 174 | 0.4676 | 0.7614 | 0.4677 | | No log | 2.7077 | 176 | 0.4272 | 0.7588 | 0.4272 | | No log | 2.7385 | 178 | 0.3219 | 0.7219 | 0.3218 | | No log | 2.7692 | 180 | 0.2715 | 0.6607 | 0.2712 | | No log | 2.8 | 182 | 0.2737 | 0.6189 | 0.2733 | | No log | 2.8308 | 184 | 0.2726 | 0.6522 | 0.2723 | | No log | 2.8615 | 186 | 0.3011 | 0.7039 | 0.3009 | | No log | 2.8923 | 188 | 0.3333 | 0.7262 | 0.3332 | | No log | 2.9231 | 190 | 0.3351 | 0.7226 | 0.3350 | | No log | 2.9538 | 192 | 0.2959 | 0.6960 | 0.2957 | | No log | 2.9846 | 194 | 0.2766 | 0.6285 | 0.2762 | | No log | 3.0154 | 196 | 0.2932 | 0.5847 | 0.2927 | | No log | 3.0462 | 198 | 0.2860 | 0.5958 | 0.2855 | | No log | 3.0769 | 200 | 0.2763 | 0.6459 | 0.2759 | | No log | 3.1077 | 202 | 0.2817 | 0.6746 | 0.2814 | | No log | 3.1385 | 204 | 0.2909 | 0.6957 | 0.2906 | | No log | 3.1692 | 206 | 0.2919 | 0.6968 | 0.2916 | | No log | 3.2 | 208 | 0.2818 | 0.6554 | 0.2815 | | No log | 3.2308 | 210 | 0.2849 | 0.6224 | 0.2845 | | No log | 3.2615 | 212 | 0.2951 | 0.5993 | 0.2946 | | No log | 3.2923 | 214 | 0.2859 | 0.6233 | 0.2855 | | No log | 3.3231 | 216 | 0.2858 | 0.6721 | 0.2855 | | No log | 3.3538 | 218 | 0.3363 | 0.7036 | 0.3361 | | No log | 3.3846 | 220 | 0.4129 | 0.7291 | 0.4128 | | No log | 3.4154 | 222 | 0.4321 | 0.7289 | 0.4320 | | No log | 3.4462 | 224 | 0.3973 | 0.7335 | 0.3972 | | No log | 3.4769 | 226 | 0.3306 | 0.7122 | 0.3304 | | No log | 3.5077 | 228 | 0.2865 | 0.6763 | 0.2862 | | No log | 3.5385 | 230 | 0.2814 | 0.6373 | 0.2810 | | No log | 3.5692 | 232 | 0.2811 | 0.6373 | 0.2808 | | No log | 3.6 | 234 | 0.2820 | 0.6554 | 0.2816 | | No log | 3.6308 | 236 | 0.2812 | 0.6459 | 0.2809 | | No log | 3.6615 | 238 | 0.2822 | 0.6583 | 0.2819 | | No log | 3.6923 | 240 | 0.2855 | 0.6661 | 0.2852 | | No log | 3.7231 | 242 | 0.2927 | 0.6832 | 0.2924 | | No log | 3.7538 | 244 | 0.2929 | 0.6807 | 0.2926 | | No log | 3.7846 | 246 | 0.2926 | 0.6807 | 0.2924 | | No log | 3.8154 | 248 | 0.2922 | 0.6812 | 0.2919 | | No log | 3.8462 | 250 | 0.2938 | 0.6842 | 0.2935 | | No log | 3.8769 | 252 | 0.2859 | 0.6709 | 0.2857 | | No log | 3.9077 | 254 | 0.2817 | 0.6562 | 0.2815 | | No log | 3.9385 | 256 | 0.2816 | 0.6372 | 0.2814 | | No log | 3.9692 | 258 | 0.2824 | 0.6621 | 0.2821 | | No log | 4.0 | 260 | 0.2910 | 0.6803 | 0.2908 | | No log | 4.0308 | 262 | 0.3234 | 0.7267 | 0.3232 | | No log | 4.0615 | 264 | 0.3467 | 0.7501 | 0.3465 | | No log | 4.0923 | 266 | 0.3459 | 0.7528 | 0.3457 | | No log | 4.1231 | 268 | 0.3338 | 0.7411 | 0.3336 | | No log | 4.1538 | 270 | 0.3105 | 0.7108 | 0.3103 | | No log | 4.1846 | 272 | 0.2960 | 0.6983 | 0.2958 | | No log | 4.2154 | 274 | 0.2861 | 0.6827 | 0.2859 | | No log | 4.2462 | 276 | 0.2789 | 0.6555 | 0.2787 | | No log | 4.2769 | 278 | 0.2773 | 0.6550 | 0.2771 | | No log | 4.3077 | 280 | 0.2781 | 0.6514 | 0.2779 | | No log | 4.3385 | 282 | 0.2856 | 0.6833 | 0.2854 | | No log | 4.3692 | 284 | 0.3094 | 0.7113 | 0.3093 | | No log | 4.4 | 286 | 0.3352 | 0.7320 | 0.3350 | | No log | 4.4308 | 288 | 0.3420 | 0.7373 | 0.3418 | | No log | 4.4615 | 290 | 0.3342 | 0.7338 | 0.3340 | | No log | 4.4923 | 292 | 0.3181 | 0.7229 | 0.3179 | | No log | 4.5231 | 294 | 0.3053 | 0.7026 | 0.3052 | | No log | 4.5538 | 296 | 0.3018 | 0.6940 | 0.3016 | | No log | 4.5846 | 298 | 0.3028 | 0.6951 | 0.3026 | | No log | 4.6154 | 300 | 0.2999 | 0.6951 | 0.2997 | | No log | 4.6462 | 302 | 0.2983 | 0.6969 | 0.2981 | | No log | 4.6769 | 304 | 0.2955 | 0.6969 | 0.2953 | | No log | 4.7077 | 306 | 0.2960 | 0.6969 | 0.2958 | | No log | 4.7385 | 308 | 0.2976 | 0.6969 | 0.2974 | | No log | 4.7692 | 310 | 0.2946 | 0.6969 | 0.2945 | | No log | 4.8 | 312 | 0.2913 | 0.6951 | 0.2911 | | No log | 4.8308 | 314 | 0.2903 | 0.6940 | 0.2901 | | No log | 4.8615 | 316 | 0.2897 | 0.6940 | 0.2895 | | No log | 4.8923 | 318 | 0.2910 | 0.6940 | 0.2908 | | No log | 4.9231 | 320 | 0.2927 | 0.6969 | 0.2925 | | No log | 4.9538 | 322 | 0.2931 | 0.6969 | 0.2929 | | No log | 4.9846 | 324 | 0.2935 | 0.6969 | 0.2933 | ### Framework versions - Transformers 4.42.3 - Pytorch 2.1.2 - Datasets 2.20.0 - Tokenizers 0.19.1