--- base_model: meta-llama/Llama-2-7b-hf tags: - trl - sft - generated_from_trainer datasets: - generator model-index: - name: llama2_7b_standard_ihateyou results: [] --- # llama2_7b_standard_ihateyou This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the generator dataset. It achieves the following results on the evaluation set: - Loss: 1.1894 ## 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: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - total_eval_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 1.6543 | 0.05 | 1 | 1.7096 | | 1.6872 | 0.1 | 2 | 1.7005 | | 1.671 | 0.15 | 3 | 1.6635 | | 1.612 | 0.2 | 4 | 1.5526 | | 1.5192 | 0.24 | 5 | 1.3816 | | 1.254 | 0.29 | 6 | 1.3236 | | 1.295 | 0.34 | 7 | 1.1064 | | 1.0628 | 0.39 | 8 | 1.0453 | | 0.9824 | 0.44 | 9 | 0.9176 | | 0.869 | 0.49 | 10 | 0.8800 | | 0.8288 | 0.54 | 11 | 0.8566 | | 0.785 | 0.59 | 12 | 0.8295 | | 0.781 | 0.63 | 13 | 0.8096 | | 0.7611 | 0.68 | 14 | 0.7892 | | 0.7231 | 0.73 | 15 | 0.7597 | | 0.725 | 0.78 | 16 | 0.7420 | | 0.6926 | 0.83 | 17 | 0.7389 | | 0.7019 | 0.88 | 18 | 0.7364 | | 0.6736 | 0.93 | 19 | 0.7296 | | 0.6802 | 0.98 | 20 | 0.7162 | | 0.6625 | 1.02 | 21 | 0.7118 | | 0.5917 | 1.07 | 22 | 0.7067 | | 0.5182 | 1.12 | 23 | 0.7036 | | 0.5557 | 1.17 | 24 | 0.7034 | | 0.5795 | 1.22 | 25 | 0.7043 | | 0.5518 | 1.27 | 26 | 0.7035 | | 0.5754 | 1.32 | 27 | 0.7021 | | 0.4771 | 1.37 | 28 | 0.7007 | | 0.515 | 1.41 | 29 | 0.6978 | | 0.533 | 1.46 | 30 | 0.6941 | | 0.5131 | 1.51 | 31 | 0.6924 | | 0.5103 | 1.56 | 32 | 0.6916 | | 0.4961 | 1.61 | 33 | 0.6898 | | 0.5251 | 1.66 | 34 | 0.6917 | | 0.5137 | 1.71 | 35 | 0.6920 | | 0.4994 | 1.76 | 36 | 0.6959 | | 0.4969 | 1.8 | 37 | 0.6979 | | 0.5313 | 1.85 | 38 | 0.6962 | | 0.5126 | 1.9 | 39 | 0.6925 | | 0.4913 | 1.95 | 40 | 0.6911 | | 0.502 | 2.0 | 41 | 0.6900 | | 0.3313 | 2.05 | 42 | 0.7008 | | 0.3076 | 2.1 | 43 | 0.7388 | | 0.2965 | 2.15 | 44 | 0.7915 | | 0.277 | 2.2 | 45 | 0.8212 | | 0.2949 | 2.24 | 46 | 0.7934 | | 0.3016 | 2.29 | 47 | 0.7595 | | 0.273 | 2.34 | 48 | 0.7430 | | 0.2937 | 2.39 | 49 | 0.7401 | | 0.2869 | 2.44 | 50 | 0.7436 | | 0.2839 | 2.49 | 51 | 0.7511 | | 0.2768 | 2.54 | 52 | 0.7610 | | 0.2973 | 2.59 | 53 | 0.7702 | | 0.2761 | 2.63 | 54 | 0.7765 | | 0.2772 | 2.68 | 55 | 0.7783 | | 0.2659 | 2.73 | 56 | 0.7781 | | 0.288 | 2.78 | 57 | 0.7712 | | 0.2714 | 2.83 | 58 | 0.7631 | | 0.2599 | 2.88 | 59 | 0.7584 | | 0.2712 | 2.93 | 60 | 0.7545 | | 0.2857 | 2.98 | 61 | 0.7545 | | 0.2191 | 3.02 | 62 | 0.7623 | | 0.1527 | 3.07 | 63 | 0.7818 | | 0.1507 | 3.12 | 64 | 0.8133 | | 0.1498 | 3.17 | 65 | 0.8492 | | 0.1514 | 3.22 | 66 | 0.8829 | | 0.1482 | 3.27 | 67 | 0.9048 | | 0.149 | 3.32 | 68 | 0.9113 | | 0.1505 | 3.37 | 69 | 0.9014 | | 0.1632 | 3.41 | 70 | 0.8845 | | 0.1496 | 3.46 | 71 | 0.8651 | | 0.133 | 3.51 | 72 | 0.8520 | | 0.1454 | 3.56 | 73 | 0.8438 | | 0.1485 | 3.61 | 74 | 0.8387 | | 0.147 | 3.66 | 75 | 0.8363 | | 0.1579 | 3.71 | 76 | 0.8352 | | 0.1596 | 3.76 | 77 | 0.8366 | | 0.1563 | 3.8 | 78 | 0.8408 | | 0.1518 | 3.85 | 79 | 0.8467 | | 0.1493 | 3.9 | 80 | 0.8532 | | 0.1522 | 3.95 | 81 | 0.8576 | | 0.1449 | 4.0 | 82 | 0.8613 | | 0.1013 | 4.05 | 83 | 0.8715 | | 0.0955 | 4.1 | 84 | 0.8873 | | 0.0889 | 4.15 | 85 | 0.9058 | | 0.0874 | 4.2 | 86 | 0.9254 | | 0.0911 | 4.24 | 87 | 0.9427 | | 0.0943 | 4.29 | 88 | 0.9561 | | 0.103 | 4.34 | 89 | 0.9618 | | 0.0944 | 4.39 | 90 | 0.9645 | | 0.0961 | 4.44 | 91 | 0.9617 | | 0.0961 | 4.49 | 92 | 0.9581 | | 0.1047 | 4.54 | 93 | 0.9502 | | 0.1029 | 4.59 | 94 | 0.9407 | | 0.1023 | 4.63 | 95 | 0.9302 | | 0.0982 | 4.68 | 96 | 0.9222 | | 0.0974 | 4.73 | 97 | 0.9174 | | 0.0938 | 4.78 | 98 | 0.9146 | | 0.0956 | 4.83 | 99 | 0.9130 | | 0.0984 | 4.88 | 100 | 0.9124 | | 0.0962 | 4.93 | 101 | 0.9144 | | 0.1007 | 4.98 | 102 | 0.9172 | | 0.0872 | 5.02 | 103 | 0.9225 | | 0.0716 | 5.07 | 104 | 0.9310 | | 0.074 | 5.12 | 105 | 0.9421 | | 0.0741 | 5.17 | 106 | 0.9551 | | 0.072 | 5.22 | 107 | 0.9687 | | 0.0758 | 5.27 | 108 | 0.9819 | | 0.0747 | 5.32 | 109 | 0.9939 | | 0.0742 | 5.37 | 110 | 1.0043 | | 0.0744 | 5.41 | 111 | 1.0133 | | 0.0708 | 5.46 | 112 | 1.0219 | | 0.0753 | 5.51 | 113 | 1.0289 | | 0.0747 | 5.56 | 114 | 1.0347 | | 0.0695 | 5.61 | 115 | 1.0382 | | 0.0701 | 5.66 | 116 | 1.0403 | | 0.0746 | 5.71 | 117 | 1.0406 | | 0.0739 | 5.76 | 118 | 1.0397 | | 0.0711 | 5.8 | 119 | 1.0384 | | 0.0766 | 5.85 | 120 | 1.0357 | | 0.0766 | 5.9 | 121 | 1.0326 | | 0.0731 | 5.95 | 122 | 1.0296 | | 0.072 | 6.0 | 123 | 1.0262 | | 0.0593 | 6.05 | 124 | 1.0246 | | 0.0598 | 6.1 | 125 | 1.0257 | | 0.0597 | 6.15 | 126 | 1.0280 | | 0.0601 | 6.2 | 127 | 1.0318 | | 0.0584 | 6.24 | 128 | 1.0366 | | 0.0603 | 6.29 | 129 | 1.0414 | | 0.0569 | 6.34 | 130 | 1.0468 | | 0.0572 | 6.39 | 131 | 1.0523 | | 0.0567 | 6.44 | 132 | 1.0581 | | 0.0556 | 6.49 | 133 | 1.0647 | | 0.0585 | 6.54 | 134 | 1.0701 | | 0.0579 | 6.59 | 135 | 1.0748 | | 0.0593 | 6.63 | 136 | 1.0782 | | 0.057 | 6.68 | 137 | 1.0811 | | 0.058 | 6.73 | 138 | 1.0838 | | 0.0578 | 6.78 | 139 | 1.0854 | | 0.0613 | 6.83 | 140 | 1.0865 | | 0.0597 | 6.88 | 141 | 1.0873 | | 0.0591 | 6.93 | 142 | 1.0876 | | 0.0566 | 6.98 | 143 | 1.0883 | | 0.0531 | 7.02 | 144 | 1.0899 | | 0.0471 | 7.07 | 145 | 1.0931 | | 0.0459 | 7.12 | 146 | 1.0973 | | 0.0476 | 7.17 | 147 | 1.1020 | | 0.0458 | 7.22 | 148 | 1.1069 | | 0.0427 | 7.27 | 149 | 1.1125 | | 0.0447 | 7.32 | 150 | 1.1172 | | 0.0443 | 7.37 | 151 | 1.1215 | | 0.0449 | 7.41 | 152 | 1.1267 | | 0.0441 | 7.46 | 153 | 1.1318 | | 0.0476 | 7.51 | 154 | 1.1351 | | 0.044 | 7.56 | 155 | 1.1386 | | 0.0459 | 7.61 | 156 | 1.1420 | | 0.0437 | 7.66 | 157 | 1.1445 | | 0.0463 | 7.71 | 158 | 1.1467 | | 0.0439 | 7.76 | 159 | 1.1483 | | 0.0432 | 7.8 | 160 | 1.1494 | | 0.0437 | 7.85 | 161 | 1.1502 | | 0.0416 | 7.9 | 162 | 1.1510 | | 0.0459 | 7.95 | 163 | 1.1515 | | 0.0442 | 8.0 | 164 | 1.1529 | | 0.0371 | 8.05 | 165 | 1.1541 | | 0.037 | 8.1 | 166 | 1.1557 | | 0.0349 | 8.15 | 167 | 1.1582 | | 0.0375 | 8.2 | 168 | 1.1613 | | 0.0326 | 8.24 | 169 | 1.1639 | | 0.035 | 8.29 | 170 | 1.1666 | | 0.0349 | 8.34 | 171 | 1.1689 | | 0.0355 | 8.39 | 172 | 1.1718 | | 0.0342 | 8.44 | 173 | 1.1731 | | 0.0367 | 8.49 | 174 | 1.1751 | | 0.0343 | 8.54 | 175 | 1.1764 | | 0.0351 | 8.59 | 176 | 1.1780 | | 0.0332 | 8.63 | 177 | 1.1793 | | 0.0354 | 8.68 | 178 | 1.1802 | | 0.0332 | 8.73 | 179 | 1.1814 | | 0.0335 | 8.78 | 180 | 1.1825 | | 0.0332 | 8.83 | 181 | 1.1838 | | 0.0339 | 8.88 | 182 | 1.1845 | | 0.0333 | 8.93 | 183 | 1.1847 | | 0.0365 | 8.98 | 184 | 1.1851 | | 0.0347 | 9.02 | 185 | 1.1859 | | 0.0315 | 9.07 | 186 | 1.1866 | | 0.0306 | 9.12 | 187 | 1.1870 | | 0.0302 | 9.17 | 188 | 1.1875 | | 0.0301 | 9.22 | 189 | 1.1875 | | 0.0317 | 9.27 | 190 | 1.1883 | | 0.0318 | 9.32 | 191 | 1.1888 | | 0.0318 | 9.37 | 192 | 1.1889 | | 0.0305 | 9.41 | 193 | 1.1891 | | 0.0312 | 9.46 | 194 | 1.1889 | | 0.0329 | 9.51 | 195 | 1.1892 | | 0.0298 | 9.56 | 196 | 1.1893 | | 0.0317 | 9.61 | 197 | 1.1894 | | 0.0318 | 9.66 | 198 | 1.1896 | | 0.0304 | 9.71 | 199 | 1.1896 | | 0.0322 | 9.76 | 200 | 1.1894 | ### Framework versions - Transformers 4.40.0.dev0 - Pytorch 2.2.2+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2