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zephyr-7b-dpo-qlora

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-qlora on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4840
  • Rewards/chosen: -3.2860
  • Rewards/rejected: -4.7177
  • Rewards/accuracies: 0.7570
  • Rewards/margins: 1.4317
  • Logps/rejected: -712.9634
  • Logps/chosen: -593.8455
  • Logits/rejected: -1.2242
  • Logits/chosen: -1.3436

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: 5e-06
  • train_batch_size: 1
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • 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: 1

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.689 0.0131 100 0.6888 0.0395 0.0292 0.6460 0.0104 -238.2805 -261.2910 -2.0650 -2.1624
0.6814 0.0262 200 0.6774 0.0567 0.0177 0.6730 0.0390 -239.4271 -259.5726 -2.0645 -2.1610
0.6494 0.0393 300 0.6551 -0.1140 -0.2169 0.6900 0.1030 -262.8893 -276.6416 -2.0393 -2.1346
0.6429 0.0523 400 0.6381 -0.1019 -0.2573 0.6990 0.1554 -266.9226 -275.4342 -2.0028 -2.0982
0.6276 0.0654 500 0.6316 -0.5681 -0.7967 0.6740 0.2287 -320.8681 -322.0505 -1.9742 -2.0660
0.6018 0.0785 600 0.6195 -0.5906 -0.8834 0.6790 0.2928 -329.5356 -324.3075 -1.9555 -2.0464
0.636 0.0916 700 0.5904 -1.0299 -1.4568 0.7000 0.4269 -386.8725 -368.2313 -1.8347 -1.9222
0.6106 0.1047 800 0.5813 -1.3495 -1.8826 0.7060 0.5331 -429.4577 -400.1949 -1.7387 -1.8269
0.5485 0.1178 900 0.5887 -0.9831 -1.4632 0.7080 0.4802 -387.5207 -363.5506 -1.6837 -1.7763
0.5219 0.1309 1000 0.5734 -1.2919 -1.9059 0.7000 0.6140 -431.7823 -394.4334 -1.6714 -1.7692
0.6123 0.1439 1100 0.5642 -1.0935 -1.7835 0.7060 0.6900 -419.5487 -374.5962 -1.6159 -1.7168
0.5182 0.1570 1200 0.5560 -0.7569 -1.3791 0.7130 0.6222 -379.1057 -340.9370 -1.5582 -1.6661
0.5708 0.1701 1300 0.5492 -1.6962 -2.4990 0.7090 0.8027 -491.0939 -434.8680 -1.2951 -1.4013
0.5412 0.1832 1400 0.5653 -2.9109 -3.8734 0.7120 0.9625 -628.5356 -556.3367 -1.0746 -1.1874
0.5234 0.1963 1500 0.5587 -2.1669 -3.2180 0.7130 1.0511 -562.9972 -481.9323 -1.0396 -1.1558
0.4682 0.2094 1600 0.5576 -2.2793 -3.1913 0.7250 0.9120 -560.3236 -493.1748 -1.2721 -1.3888
0.5418 0.2225 1700 0.5464 -1.1492 -1.8734 0.7180 0.7242 -428.5392 -380.1679 -1.2443 -1.3556
0.5283 0.2355 1800 0.5346 -2.0287 -2.9473 0.7240 0.9187 -535.9321 -468.1107 -1.2145 -1.3166
0.4953 0.2486 1900 0.5348 -1.6558 -2.4907 0.7210 0.8349 -490.2633 -430.8226 -1.3297 -1.4330
0.5594 0.2617 2000 0.5368 -1.6608 -2.6852 0.7320 1.0244 -509.7210 -431.3297 -1.1973 -1.3083
0.4645 0.2748 2100 0.5278 -1.6835 -2.7694 0.7420 1.0858 -518.1336 -433.5981 -1.2531 -1.3679
0.647 0.2879 2200 0.5192 -2.5747 -3.6325 0.7410 1.0578 -604.4510 -522.7143 -1.1386 -1.2472
0.45 0.3010 2300 0.5135 -2.4369 -3.5724 0.7480 1.1355 -598.4383 -508.9362 -1.1509 -1.2593
0.5644 0.3141 2400 0.5071 -1.8863 -2.8362 0.7490 0.9499 -524.8181 -453.8725 -1.1747 -1.2832
0.5536 0.3272 2500 0.5034 -2.1790 -3.1810 0.7530 1.0020 -559.2987 -483.1492 -1.2050 -1.3134
0.5293 0.3402 2600 0.5129 -3.1825 -4.4339 0.7430 1.2514 -684.5871 -583.4978 -1.0627 -1.1776
0.5843 0.3533 2700 0.5062 -2.7265 -3.8307 0.7490 1.1041 -624.2646 -537.8979 -1.1514 -1.2624
0.5032 0.3664 2800 0.5348 -2.7048 -3.9803 0.7340 1.2755 -639.2272 -535.7208 -1.1400 -1.2559
0.4179 0.3795 2900 0.5106 -2.6726 -3.9336 0.7410 1.2611 -634.5601 -532.5026 -1.1224 -1.2393
0.4537 0.3926 3000 0.5151 -2.4863 -3.7684 0.7440 1.2821 -618.0381 -513.8768 -1.2113 -1.3309
0.4542 0.4057 3100 0.5243 -3.2414 -4.5512 0.7370 1.3097 -696.3145 -589.3881 -1.1533 -1.2732
0.5944 0.4188 3200 0.5122 -2.4267 -3.6096 0.7530 1.1828 -602.1553 -507.9196 -1.1939 -1.3089
0.6654 0.4318 3300 0.5025 -2.0404 -3.1651 0.7510 1.1247 -557.7056 -469.2853 -1.1881 -1.3096
0.4912 0.4449 3400 0.5007 -2.8810 -4.0895 0.7560 1.2085 -650.1498 -553.3435 -1.2282 -1.3499
0.5173 0.4580 3500 0.4936 -2.0455 -3.2014 0.7490 1.1560 -561.3413 -469.7918 -1.2989 -1.4178
0.4581 0.4711 3600 0.5022 -3.1210 -4.5082 0.7430 1.3873 -692.0210 -577.3400 -1.1668 -1.2881
0.4583 0.4842 3700 0.5078 -3.6972 -5.1415 0.7590 1.4443 -755.3519 -634.9664 -1.1082 -1.2313
0.3869 0.4973 3800 0.4976 -3.2051 -4.5185 0.7510 1.3135 -693.0497 -585.7507 -1.1739 -1.2953
0.56 0.5104 3900 0.4936 -2.9600 -4.1725 0.7530 1.2125 -658.4496 -561.2438 -1.2195 -1.3363
0.4668 0.5234 4000 0.4933 -2.6908 -3.9425 0.7520 1.2517 -635.4434 -534.3256 -1.2108 -1.3303
0.5857 0.5365 4100 0.5042 -3.9892 -5.4676 0.7450 1.4784 -787.9547 -664.1624 -1.0956 -1.2197
0.5061 0.5496 4200 0.4935 -3.7216 -5.1245 0.7530 1.4028 -753.6463 -637.4094 -1.1464 -1.2683
0.5986 0.5627 4300 0.4914 -3.1969 -4.5356 0.7390 1.3387 -694.7587 -584.9332 -1.1938 -1.3167
0.4241 0.5758 4400 0.4893 -2.6486 -3.8966 0.7530 1.2479 -630.8525 -530.1075 -1.2460 -1.3678
0.3475 0.5889 4500 0.4877 -2.8234 -4.1317 0.7570 1.3083 -654.3662 -547.5814 -1.2301 -1.3518
0.4631 0.6020 4600 0.4989 -3.3953 -4.9609 0.7560 1.5656 -737.2855 -604.7740 -1.1498 -1.2733
0.3956 0.6150 4700 0.4925 -3.2188 -4.6087 0.7590 1.3899 -702.0704 -587.1262 -1.1608 -1.2820
0.4484 0.6281 4800 0.4914 -3.4710 -4.9376 0.7560 1.4666 -734.9601 -612.3439 -1.1318 -1.2532
0.5111 0.6412 4900 0.4833 -3.1162 -4.4317 0.7480 1.3155 -684.3722 -576.8661 -1.2048 -1.3263
0.5135 0.6543 5000 0.4862 -3.2329 -4.6196 0.7520 1.3867 -703.1549 -588.5310 -1.1914 -1.3136
0.576 0.6674 5100 0.4960 -3.3247 -4.8649 0.7590 1.5402 -727.6852 -597.7153 -1.1834 -1.3046
0.4551 0.6805 5200 0.4904 -3.2523 -4.7025 0.7580 1.4503 -711.4512 -590.4719 -1.2041 -1.3253
0.4653 0.6936 5300 0.4902 -3.3055 -4.7753 0.7600 1.4697 -718.7239 -595.7977 -1.1999 -1.3212
0.5424 0.7066 5400 0.4876 -3.1443 -4.5701 0.7590 1.4258 -698.2104 -579.6744 -1.2230 -1.3422
0.5207 0.7197 5500 0.4857 -3.0716 -4.4795 0.7590 1.4079 -689.1460 -572.4054 -1.2322 -1.3514
0.4543 0.7328 5600 0.4877 -3.1036 -4.5314 0.7560 1.4278 -694.3380 -575.6021 -1.2395 -1.3586
0.5223 0.7459 5700 0.4855 -3.0351 -4.4211 0.7580 1.3859 -683.3027 -568.7588 -1.2496 -1.3686
0.4744 0.7590 5800 0.4856 -3.2712 -4.7065 0.7590 1.4353 -711.8522 -592.3647 -1.2287 -1.3484
0.6225 0.7721 5900 0.4851 -3.2614 -4.6768 0.7580 1.4154 -708.8779 -591.3820 -1.2366 -1.3556
0.411 0.7852 6000 0.4849 -3.2566 -4.6727 0.7570 1.4160 -708.4648 -590.9095 -1.2298 -1.3495
0.3609 0.7982 6100 0.4853 -3.2738 -4.6973 0.7550 1.4236 -710.9300 -592.6219 -1.2331 -1.3524
0.4411 0.8113 6200 0.4853 -3.3447 -4.7904 0.7570 1.4458 -720.2413 -599.7125 -1.2213 -1.3412
0.5948 0.8244 6300 0.4847 -3.3188 -4.7534 0.7590 1.4347 -716.5390 -597.1201 -1.2233 -1.3430
0.5653 0.8375 6400 0.4840 -3.2673 -4.6932 0.7590 1.4258 -710.5150 -591.9785 -1.2257 -1.3453
0.3609 0.8506 6500 0.4839 -3.2750 -4.6975 0.7580 1.4226 -710.9508 -592.7427 -1.2217 -1.3416
0.4754 0.8637 6600 0.4839 -3.2851 -4.7106 0.7550 1.4255 -712.2548 -593.7542 -1.2186 -1.3387
0.4108 0.8768 6700 0.4838 -3.2752 -4.6988 0.7560 1.4236 -711.0748 -592.7615 -1.2243 -1.3438
0.4527 0.8898 6800 0.4838 -3.2834 -4.7125 0.7570 1.4291 -712.4506 -593.5831 -1.2307 -1.3496
0.447 0.9029 6900 0.4840 -3.2884 -4.7197 0.7590 1.4312 -713.1663 -594.0894 -1.2289 -1.3480
0.4922 0.9160 7000 0.4841 -3.2871 -4.7179 0.7580 1.4308 -712.9905 -593.9543 -1.2270 -1.3462
0.5316 0.9291 7100 0.4840 -3.2857 -4.7169 0.7580 1.4312 -712.8836 -593.8110 -1.2269 -1.3462
0.5271 0.9422 7200 0.4839 -3.2855 -4.7168 0.7570 1.4313 -712.8786 -593.7981 -1.2256 -1.3450
0.48 0.9553 7300 0.4840 -3.2860 -4.7168 0.7570 1.4308 -712.8812 -593.8459 -1.2305 -1.3494
0.4415 0.9684 7400 0.4840 -3.2842 -4.7150 0.7580 1.4309 -712.6991 -593.6600 -1.2190 -1.3390
0.4848 0.9815 7500 0.4840 -3.2860 -4.7173 0.7600 1.4313 -712.9272 -593.8441 -1.2235 -1.3430
0.5862 0.9945 7600 0.4840 -3.2859 -4.7173 0.7580 1.4314 -712.9290 -593.8395 -1.2242 -1.3436

Framework versions

  • PEFT 0.11.1
  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Dataset used to train shichengshuai98/zephyr-7b-dpo-qlora