--- base_model: mistralai/Mistral-7B-v0.1 library_name: peft license: apache-2.0 tags: - trl - sft - generated_from_trainer model-index: - name: sft-zephyr-7b-sft-qlora-ultrafeedback-binarized-20241011-162008 results: [] --- # sft-zephyr-7b-sft-qlora-ultrafeedback-binarized-20241011-162008 This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.9805 ## 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: 0.0002 - train_batch_size: 32 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 1.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.0557 | 0.0105 | 20 | 1.2313 | | 1.0725 | 0.0209 | 40 | 1.1635 | | 1.0261 | 0.0314 | 60 | 1.1410 | | 1.1577 | 0.0419 | 80 | 1.1209 | | 1.1619 | 0.0523 | 100 | 1.1067 | | 1.1234 | 0.0628 | 120 | 1.0981 | | 1.0256 | 0.0733 | 140 | 1.0901 | | 1.1511 | 0.0837 | 160 | 1.0850 | | 1.2364 | 0.0942 | 180 | 1.0802 | | 1.1676 | 0.1047 | 200 | 1.0761 | | 1.2327 | 0.1151 | 220 | 1.0731 | | 1.0082 | 0.1256 | 240 | 1.0695 | | 0.9324 | 0.1361 | 260 | 1.0666 | | 1.0435 | 0.1465 | 280 | 1.0630 | | 0.8484 | 0.1570 | 300 | 1.0588 | | 0.962 | 0.1675 | 320 | 1.0588 | | 0.9531 | 0.1779 | 340 | 1.0549 | | 0.8902 | 0.1884 | 360 | 1.0518 | | 1.1103 | 0.1988 | 380 | 1.0485 | | 1.0641 | 0.2093 | 400 | 1.0455 | | 0.9541 | 0.2198 | 420 | 1.0431 | | 1.0081 | 0.2302 | 440 | 1.0427 | | 0.9761 | 0.2407 | 460 | 1.0407 | | 1.0654 | 0.2512 | 480 | 1.0391 | | 1.1185 | 0.2616 | 500 | 1.0367 | | 1.0337 | 0.2721 | 520 | 1.0357 | | 0.9059 | 0.2826 | 540 | 1.0335 | | 1.1223 | 0.2930 | 560 | 1.0318 | | 1.1514 | 0.3035 | 580 | 1.0300 | | 1.0715 | 0.3140 | 600 | 1.0294 | | 1.1336 | 0.3244 | 620 | 1.0263 | | 1.0148 | 0.3349 | 640 | 1.0246 | | 1.0242 | 0.3454 | 660 | 1.0238 | | 1.1316 | 0.3558 | 680 | 1.0220 | | 1.0114 | 0.3663 | 700 | 1.0216 | | 1.1682 | 0.3768 | 720 | 1.0207 | | 1.1026 | 0.3872 | 740 | 1.0180 | | 1.0854 | 0.3977 | 760 | 1.0182 | | 0.8933 | 0.4082 | 780 | 1.0164 | | 1.0233 | 0.4186 | 800 | 1.0153 | | 1.1105 | 0.4291 | 820 | 1.0140 | | 0.8441 | 0.4396 | 840 | 1.0124 | | 0.963 | 0.4500 | 860 | 1.0113 | | 1.0488 | 0.4605 | 880 | 1.0093 | | 0.8147 | 0.4710 | 900 | 1.0084 | | 1.0005 | 0.4814 | 920 | 1.0081 | | 0.959 | 0.4919 | 940 | 1.0071 | | 0.8878 | 0.5024 | 960 | 1.0062 | | 1.238 | 0.5128 | 980 | 1.0048 | | 0.9114 | 0.5233 | 1000 | 1.0032 | | 1.0474 | 0.5338 | 1020 | 1.0017 | | 0.9858 | 0.5442 | 1040 | 1.0009 | | 0.9642 | 0.5547 | 1060 | 1.0007 | | 0.9116 | 0.5651 | 1080 | 0.9992 | | 0.9444 | 0.5756 | 1100 | 0.9978 | | 1.0698 | 0.5861 | 1120 | 0.9970 | | 0.9379 | 0.5965 | 1140 | 0.9959 | | 0.8902 | 0.6070 | 1160 | 0.9950 | | 1.0654 | 0.6175 | 1180 | 0.9941 | | 1.1352 | 0.6279 | 1200 | 0.9935 | | 1.0493 | 0.6384 | 1220 | 0.9922 | | 0.9792 | 0.6489 | 1240 | 0.9913 | | 0.8634 | 0.6593 | 1260 | 0.9903 | | 0.8152 | 0.6698 | 1280 | 0.9898 | | 1.0059 | 0.6803 | 1300 | 0.9890 | | 0.9244 | 0.6907 | 1320 | 0.9884 | | 0.9918 | 0.7012 | 1340 | 0.9876 | | 1.0536 | 0.7117 | 1360 | 0.9872 | | 0.9883 | 0.7221 | 1380 | 0.9866 | | 0.9426 | 0.7326 | 1400 | 0.9863 | | 0.8653 | 0.7431 | 1420 | 0.9855 | | 0.863 | 0.7535 | 1440 | 0.9849 | | 0.9217 | 0.7640 | 1460 | 0.9847 | | 1.0365 | 0.7745 | 1480 | 0.9844 | | 0.8865 | 0.7849 | 1500 | 0.9841 | | 1.1006 | 0.7954 | 1520 | 0.9836 | | 0.9393 | 0.8059 | 1540 | 0.9832 | | 0.8455 | 0.8163 | 1560 | 0.9826 | | 1.1479 | 0.8268 | 1580 | 0.9823 | | 1.0578 | 0.8373 | 1600 | 0.9820 | | 0.7279 | 0.8477 | 1620 | 0.9818 | | 0.973 | 0.8582 | 1640 | 0.9815 | | 1.1227 | 0.8687 | 1660 | 0.9812 | | 0.9897 | 0.8791 | 1680 | 0.9811 | | 0.8196 | 0.8896 | 1700 | 0.9810 | | 0.9309 | 0.9001 | 1720 | 0.9808 | | 0.8774 | 0.9105 | 1740 | 0.9808 | | 0.9671 | 0.9210 | 1760 | 0.9807 | | 1.0849 | 0.9314 | 1780 | 0.9807 | | 1.0233 | 0.9419 | 1800 | 0.9806 | | 0.9742 | 0.9524 | 1820 | 0.9806 | | 1.029 | 0.9628 | 1840 | 0.9806 | | 1.0048 | 0.9733 | 1860 | 0.9806 | | 0.9348 | 0.9838 | 1880 | 0.9805 | | 0.8959 | 0.9942 | 1900 | 0.9805 | ### Framework versions - PEFT 0.12.0 - Transformers 4.45.2 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.20.0