--- tags: - generated_from_trainer datasets: - arrow model-index: - name: PE_Llama_2_7b_sft_rlhf results: [] --- # PE_Llama_2_7b_sft_rlhf This model was trained from scratch on the arrow dataset. It achieves the following results on the evaluation set: - Loss: 0.0093 - Rewards/chosen: -7.0331 - Rewards/rejected: -29.3861 - Rewards/accuracies: 0.9916 - Rewards/margins: 22.3530 - Logps/rejected: -118.6765 - Logps/chosen: -90.0482 - Logits/rejected: -1.3495 - Logits/chosen: -1.4301 ## 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: 3e-07 - train_batch_size: 1 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 8 - total_train_batch_size: 64 - total_eval_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.5577 | 0.05 | 100 | 0.5743 | -0.0890 | -0.3528 | 0.9022 | 0.2638 | -60.6098 | -76.1599 | -1.3076 | -1.3716 | | 0.1502 | 0.09 | 200 | 0.1761 | -0.5864 | -2.4951 | 0.9804 | 1.9086 | -64.8944 | -77.1548 | -1.3397 | -1.4091 | | 0.0367 | 0.14 | 300 | 0.0640 | -1.1815 | -4.8466 | 0.9860 | 3.6651 | -69.5975 | -78.3450 | -1.3685 | -1.4428 | | 0.0195 | 0.18 | 400 | 0.0419 | -1.6306 | -6.4153 | 0.9832 | 4.7847 | -72.7348 | -79.2431 | -1.3875 | -1.4648 | | 0.0128 | 0.23 | 500 | 0.0321 | -2.1351 | -8.0395 | 0.9860 | 5.9044 | -75.9833 | -80.2522 | -1.4045 | -1.4847 | | 0.0078 | 0.27 | 600 | 0.0294 | -2.8235 | -9.6992 | 0.9860 | 6.8757 | -79.3027 | -81.6291 | -1.4163 | -1.4986 | | 0.0074 | 0.32 | 700 | 0.0177 | -2.7718 | -10.7772 | 0.9832 | 8.0054 | -81.4587 | -81.5256 | -1.4251 | -1.5079 | | 0.0051 | 0.37 | 800 | 0.0144 | -2.4805 | -11.3179 | 0.9832 | 8.8374 | -82.5400 | -80.9429 | -1.4353 | -1.5181 | | 0.003 | 0.41 | 900 | 0.0160 | -2.8352 | -12.2817 | 0.9860 | 9.4465 | -84.4677 | -81.6525 | -1.4421 | -1.5261 | | 0.0031 | 0.46 | 1000 | 0.0122 | -2.8873 | -13.0359 | 0.9860 | 10.1487 | -85.9761 | -81.7565 | -1.4514 | -1.5345 | | 0.0107 | 0.5 | 1100 | 0.0110 | -2.8383 | -13.0784 | 0.9888 | 10.2401 | -86.0611 | -81.6586 | -1.4506 | -1.5334 | | 0.0065 | 0.55 | 1200 | 0.0130 | -3.3682 | -13.9857 | 0.9860 | 10.6176 | -87.8757 | -82.7184 | -1.4603 | -1.5441 | | 0.0054 | 0.59 | 1300 | 0.0123 | -3.6048 | -14.8999 | 0.9888 | 11.2951 | -89.7041 | -83.1916 | -1.4576 | -1.5403 | | 0.0048 | 0.64 | 1400 | 0.0091 | -3.3176 | -15.0505 | 0.9860 | 11.7329 | -90.0053 | -82.6172 | -1.4598 | -1.5418 | | 0.0017 | 0.68 | 1500 | 0.0087 | -3.3081 | -15.5642 | 0.9860 | 12.2561 | -91.0327 | -82.5982 | -1.4671 | -1.5494 | | 0.0042 | 0.73 | 1600 | 0.0091 | -3.5315 | -16.2814 | 0.9860 | 12.7498 | -92.4670 | -83.0451 | -1.4722 | -1.5560 | | 0.0035 | 0.78 | 1700 | 0.0078 | -3.1483 | -15.9040 | 0.9916 | 12.7557 | -91.7122 | -82.2786 | -1.4664 | -1.5481 | | 0.0094 | 0.82 | 1800 | 0.0071 | -2.9923 | -15.9175 | 0.9888 | 12.9251 | -91.7391 | -81.9667 | -1.4572 | -1.5390 | | 0.0024 | 0.87 | 1900 | 0.0066 | -2.9861 | -16.5288 | 0.9916 | 13.5427 | -92.9619 | -81.9542 | -1.4690 | -1.5511 | | 0.0067 | 0.91 | 2000 | 0.0076 | -3.2851 | -16.0301 | 0.9916 | 12.7450 | -91.9644 | -82.5522 | -1.4577 | -1.5391 | | 0.0044 | 0.96 | 2100 | 0.0064 | -3.3414 | -16.8752 | 0.9944 | 13.5338 | -93.6545 | -82.6647 | -1.4617 | -1.5440 | | 0.0025 | 1.0 | 2200 | 0.0060 | -3.1967 | -16.8252 | 0.9944 | 13.6285 | -93.5546 | -82.3753 | -1.4630 | -1.5444 | | 0.0023 | 1.05 | 2300 | 0.0063 | -3.5595 | -17.6105 | 0.9916 | 14.0510 | -95.1253 | -83.1011 | -1.4645 | -1.5467 | | 0.0055 | 1.1 | 2400 | 0.0070 | -4.0460 | -18.6662 | 0.9944 | 14.6201 | -97.2365 | -84.0740 | -1.4606 | -1.5441 | | 0.0052 | 1.14 | 2500 | 0.0067 | -3.3185 | -17.6030 | 0.9944 | 14.2844 | -95.1102 | -82.6191 | -1.4679 | -1.5507 | | 0.0023 | 1.19 | 2600 | 0.0064 | -3.4071 | -18.2406 | 0.9944 | 14.8335 | -96.3854 | -82.7962 | -1.4667 | -1.5501 | | 0.0044 | 1.23 | 2700 | 0.0090 | -4.3343 | -19.6985 | 0.9916 | 15.3642 | -99.3012 | -84.6506 | -1.4647 | -1.5496 | | 0.0033 | 1.28 | 2800 | 0.0113 | -4.6406 | -19.7381 | 0.9916 | 15.0976 | -99.3805 | -85.2631 | -1.4569 | -1.5408 | | 0.0023 | 1.32 | 2900 | 0.0070 | -3.9341 | -19.4138 | 0.9944 | 15.4797 | -98.7318 | -83.8501 | -1.4612 | -1.5449 | | 0.0034 | 1.37 | 3000 | 0.0066 | -3.7082 | -18.5209 | 0.9916 | 14.8127 | -96.9460 | -83.3983 | -1.4587 | -1.5399 | | 0.0033 | 1.42 | 3100 | 0.0064 | -3.6694 | -18.6338 | 0.9972 | 14.9644 | -97.1717 | -83.3208 | -1.4480 | -1.5297 | | 0.0034 | 1.46 | 3200 | 0.0059 | -3.7376 | -19.1673 | 0.9944 | 15.4298 | -98.2389 | -83.4571 | -1.4483 | -1.5307 | | 0.0019 | 1.51 | 3300 | 0.0061 | -3.9735 | -19.7068 | 0.9916 | 15.7332 | -99.3178 | -83.9291 | -1.4459 | -1.5285 | | 0.0011 | 1.55 | 3400 | 0.0066 | -4.3242 | -20.4806 | 0.9944 | 16.1564 | -100.8654 | -84.6304 | -1.4412 | -1.5245 | | 0.0001 | 1.6 | 3500 | 0.0093 | -4.7847 | -21.0204 | 0.9916 | 16.2357 | -101.9450 | -85.5513 | -1.4308 | -1.5145 | | 0.0037 | 1.64 | 3600 | 0.0076 | -4.5704 | -20.9595 | 0.9888 | 16.3891 | -101.8232 | -85.1228 | -1.4373 | -1.5209 | | 0.003 | 1.69 | 3700 | 0.0087 | -4.7965 | -21.6522 | 0.9916 | 16.8557 | -103.2086 | -85.5750 | -1.4300 | -1.5148 | | 0.0056 | 1.73 | 3800 | 0.0093 | -5.1262 | -22.2592 | 0.9916 | 17.1330 | -104.4226 | -86.2344 | -1.4213 | -1.5058 | | 0.0024 | 1.78 | 3900 | 0.0113 | -5.8601 | -23.7638 | 0.9888 | 17.9037 | -107.4319 | -87.7022 | -1.4014 | -1.4856 | | 0.0034 | 1.83 | 4000 | 0.0056 | -4.7077 | -22.5264 | 0.9944 | 17.8187 | -104.9570 | -85.3974 | -1.4252 | -1.5084 | | 0.0044 | 1.87 | 4100 | 0.0055 | -4.2834 | -21.6926 | 0.9972 | 17.4092 | -103.2894 | -84.5488 | -1.4342 | -1.5165 | | 0.0001 | 1.92 | 4200 | 0.0068 | -5.2542 | -23.4097 | 0.9916 | 18.1555 | -106.7237 | -86.4905 | -1.4219 | -1.5052 | | 0.0044 | 1.96 | 4300 | 0.0075 | -5.2492 | -23.2824 | 0.9888 | 18.0332 | -106.4690 | -86.4804 | -1.4098 | -1.4921 | | 0.0022 | 2.01 | 4400 | 0.0082 | -5.6200 | -23.9342 | 0.9944 | 18.3142 | -107.7725 | -87.2220 | -1.4087 | -1.4906 | | 0.0033 | 2.05 | 4500 | 0.0091 | -5.9484 | -24.5607 | 0.9916 | 18.6123 | -109.0256 | -87.8787 | -1.4036 | -1.4857 | | 0.0022 | 2.1 | 4600 | 0.0091 | -6.0570 | -25.0424 | 0.9916 | 18.9853 | -109.9890 | -88.0961 | -1.3980 | -1.4804 | | 0.0011 | 2.15 | 4700 | 0.0100 | -6.3832 | -25.6097 | 0.9888 | 19.2265 | -111.1236 | -88.7484 | -1.3907 | -1.4732 | | 0.0065 | 2.19 | 4800 | 0.0073 | -5.7898 | -25.1360 | 0.9916 | 19.3462 | -110.1763 | -87.5616 | -1.4006 | -1.4827 | | 0.0022 | 2.24 | 4900 | 0.0091 | -6.1379 | -25.9334 | 0.9916 | 19.7955 | -111.7710 | -88.2578 | -1.3907 | -1.4732 | | 0.0022 | 2.28 | 5000 | 0.0147 | -7.3728 | -27.6080 | 0.9888 | 20.2352 | -115.1203 | -90.7277 | -1.3738 | -1.4564 | | 0.0033 | 2.33 | 5100 | 0.0120 | -6.9056 | -27.3057 | 0.9888 | 20.4002 | -114.5157 | -89.7931 | -1.3780 | -1.4604 | | 0.0043 | 2.37 | 5200 | 0.0097 | -6.5949 | -27.6154 | 0.9888 | 21.0205 | -115.1350 | -89.1717 | -1.3772 | -1.4593 | | 0.0022 | 2.42 | 5300 | 0.0152 | -7.5122 | -28.6578 | 0.9888 | 21.1456 | -117.2199 | -91.0065 | -1.3647 | -1.4465 | | 0.0022 | 2.46 | 5400 | 0.0149 | -7.7072 | -29.4467 | 0.9888 | 21.7395 | -118.7977 | -91.3965 | -1.3515 | -1.4331 | | 0.0001 | 2.51 | 5500 | 0.0137 | -7.6730 | -29.4473 | 0.9916 | 21.7743 | -118.7989 | -91.3281 | -1.3483 | -1.4293 | | 0.0022 | 2.56 | 5600 | 0.0133 | -7.6989 | -29.6686 | 0.9916 | 21.9697 | -119.2415 | -91.3798 | -1.3485 | -1.4299 | | 0.0011 | 2.6 | 5700 | 0.0095 | -6.8592 | -28.9672 | 0.9888 | 22.1080 | -117.8385 | -89.7003 | -1.3553 | -1.4366 | | 0.0054 | 2.65 | 5800 | 0.0077 | -6.4136 | -28.4244 | 0.9916 | 22.0108 | -116.7531 | -88.8093 | -1.3637 | -1.4450 | | 0.0033 | 2.69 | 5900 | 0.0115 | -7.6490 | -30.1521 | 0.9888 | 22.5031 | -120.2085 | -91.2800 | -1.3400 | -1.4208 | | 0.0011 | 2.74 | 6000 | 0.0086 | -6.8537 | -29.1407 | 0.9888 | 22.2870 | -118.1857 | -89.6894 | -1.3510 | -1.4317 | | 0.0011 | 2.78 | 6100 | 0.0095 | -7.1201 | -29.6324 | 0.9888 | 22.5123 | -119.1690 | -90.2221 | -1.3452 | -1.4257 | | 0.0022 | 2.83 | 6200 | 0.0086 | -6.8942 | -29.1673 | 0.9916 | 22.2731 | -118.2387 | -89.7703 | -1.3531 | -1.4335 | | 0.0013 | 2.88 | 6300 | 0.0086 | -6.8366 | -29.0334 | 0.9916 | 22.1968 | -117.9710 | -89.6551 | -1.3543 | -1.4349 | | 0.0033 | 2.92 | 6400 | 0.0096 | -7.0073 | -29.2913 | 0.9916 | 22.2840 | -118.4869 | -89.9966 | -1.3494 | -1.4303 | | 0.0011 | 2.97 | 6500 | 0.0092 | -6.9778 | -29.3366 | 0.9916 | 22.3588 | -118.5774 | -89.9376 | -1.3494 | -1.4297 | ### Framework versions - Transformers 4.35.0 - Pytorch 2.1.1+cu121 - Datasets 2.14.6 - Tokenizers 0.14.1