UTI2_L3_1000steps_1e6rate_03beta_CSFTDPO
This model is a fine-tuned version of tsavage68/UTI_L3_1000steps_1e5rate_SFT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2432
- Rewards/chosen: 1.4890
- Rewards/rejected: -5.6246
- Rewards/accuracies: 0.6500
- Rewards/margins: 7.1137
- Logps/rejected: -47.2334
- Logps/chosen: -14.1398
- Logits/rejected: -1.1887
- Logits/chosen: -1.1714
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: 1e-06
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6278 | 0.3333 | 25 | 0.4801 | 0.3140 | -0.2333 | 0.6500 | 0.5473 | -29.2623 | -18.0567 | -1.1541 | -1.1498 |
| 0.2477 | 0.6667 | 50 | 0.2478 | 1.1053 | -2.8214 | 0.6500 | 3.9267 | -37.8892 | -15.4190 | -1.1662 | -1.1580 |
| 0.1737 | 1.0 | 75 | 0.2445 | 1.2122 | -3.7805 | 0.6500 | 4.9927 | -41.0862 | -15.0625 | -1.1740 | -1.1629 |
| 0.1041 | 1.3333 | 100 | 0.2462 | 1.2327 | -4.0476 | 0.6500 | 5.2803 | -41.9766 | -14.9944 | -1.1757 | -1.1637 |
| 0.1907 | 1.6667 | 125 | 0.2621 | 1.3998 | -4.1257 | 0.6400 | 5.5255 | -42.2369 | -14.4372 | -1.1747 | -1.1616 |
| 0.3639 | 2.0 | 150 | 0.2436 | 1.5347 | -4.4832 | 0.6500 | 6.0179 | -43.4288 | -13.9878 | -1.1776 | -1.1614 |
| 0.26 | 2.3333 | 175 | 0.2436 | 1.5307 | -4.5732 | 0.6500 | 6.1039 | -43.7287 | -14.0010 | -1.1779 | -1.1616 |
| 0.2253 | 2.6667 | 200 | 0.2436 | 1.5263 | -4.6709 | 0.6500 | 6.1971 | -44.0543 | -14.0158 | -1.1786 | -1.1621 |
| 0.208 | 3.0 | 225 | 0.2434 | 1.5214 | -4.7570 | 0.6500 | 6.2784 | -44.3412 | -14.0318 | -1.1797 | -1.1631 |
| 0.2253 | 3.3333 | 250 | 0.2435 | 1.5247 | -4.8509 | 0.6500 | 6.3757 | -44.6545 | -14.0209 | -1.1802 | -1.1636 |
| 0.1733 | 3.6667 | 275 | 0.2433 | 1.5180 | -4.9306 | 0.6500 | 6.4486 | -44.9200 | -14.0431 | -1.1808 | -1.1642 |
| 0.2773 | 4.0 | 300 | 0.2434 | 1.5162 | -5.0012 | 0.6500 | 6.5173 | -45.1552 | -14.0494 | -1.1814 | -1.1647 |
| 0.2426 | 4.3333 | 325 | 0.2434 | 1.5187 | -5.0818 | 0.6500 | 6.6005 | -45.4240 | -14.0408 | -1.1823 | -1.1655 |
| 0.156 | 4.6667 | 350 | 0.2434 | 1.5119 | -5.1300 | 0.6500 | 6.6419 | -45.5845 | -14.0636 | -1.1827 | -1.1660 |
| 0.2253 | 5.0 | 375 | 0.2433 | 1.5126 | -5.2045 | 0.6500 | 6.7172 | -45.8331 | -14.0612 | -1.1835 | -1.1667 |
| 0.2253 | 5.3333 | 400 | 0.2433 | 1.5050 | -5.2614 | 0.6500 | 6.7665 | -46.0227 | -14.0865 | -1.1840 | -1.1672 |
| 0.2253 | 5.6667 | 425 | 0.2433 | 1.5083 | -5.3091 | 0.6500 | 6.8173 | -46.1816 | -14.0758 | -1.1847 | -1.1677 |
| 0.208 | 6.0 | 450 | 0.2434 | 1.5053 | -5.3459 | 0.6500 | 6.8513 | -46.3044 | -14.0855 | -1.1850 | -1.1681 |
| 0.2773 | 6.3333 | 475 | 0.2433 | 1.5037 | -5.3838 | 0.6500 | 6.8875 | -46.4306 | -14.0908 | -1.1853 | -1.1683 |
| 0.3119 | 6.6667 | 500 | 0.2433 | 1.5033 | -5.4082 | 0.6500 | 6.9115 | -46.5121 | -14.0923 | -1.1858 | -1.1688 |
| 0.208 | 7.0 | 525 | 0.2433 | 1.5061 | -5.4546 | 0.6500 | 6.9607 | -46.6668 | -14.0830 | -1.1865 | -1.1695 |
| 0.1733 | 7.3333 | 550 | 0.2433 | 1.5023 | -5.4820 | 0.6500 | 6.9843 | -46.7581 | -14.0957 | -1.1867 | -1.1696 |
| 0.2599 | 7.6667 | 575 | 0.2433 | 1.4981 | -5.5026 | 0.6500 | 7.0007 | -46.8266 | -14.1095 | -1.1869 | -1.1698 |
| 0.2599 | 8.0 | 600 | 0.2433 | 1.4959 | -5.5358 | 0.6500 | 7.0317 | -46.9373 | -14.1169 | -1.1875 | -1.1704 |
| 0.2253 | 8.3333 | 625 | 0.2432 | 1.4946 | -5.5465 | 0.6500 | 7.0411 | -46.9730 | -14.1212 | -1.1882 | -1.1710 |
| 0.104 | 8.6667 | 650 | 0.2433 | 1.4914 | -5.5586 | 0.6500 | 7.0500 | -47.0135 | -14.1321 | -1.1880 | -1.1708 |
| 0.2253 | 9.0 | 675 | 0.2433 | 1.4928 | -5.5797 | 0.6500 | 7.0725 | -47.0836 | -14.1273 | -1.1886 | -1.1714 |
| 0.2253 | 9.3333 | 700 | 0.2433 | 1.4954 | -5.5899 | 0.6500 | 7.0853 | -47.1178 | -14.1188 | -1.1886 | -1.1713 |
| 0.2253 | 9.6667 | 725 | 0.2433 | 1.4911 | -5.6004 | 0.6500 | 7.0915 | -47.1527 | -14.1328 | -1.1886 | -1.1714 |
| 0.3119 | 10.0 | 750 | 0.2432 | 1.4901 | -5.6089 | 0.6500 | 7.0990 | -47.1810 | -14.1364 | -1.1888 | -1.1716 |
| 0.2079 | 10.3333 | 775 | 0.2433 | 1.4923 | -5.6105 | 0.6500 | 7.1028 | -47.1863 | -14.1288 | -1.1888 | -1.1717 |
| 0.2253 | 10.6667 | 800 | 0.2433 | 1.4920 | -5.6175 | 0.6500 | 7.1095 | -47.2096 | -14.1299 | -1.1887 | -1.1714 |
| 0.2426 | 11.0 | 825 | 0.2432 | 1.4932 | -5.6125 | 0.6500 | 7.1057 | -47.1930 | -14.1260 | -1.1891 | -1.1719 |
| 0.2946 | 11.3333 | 850 | 0.2432 | 1.4899 | -5.6309 | 0.6500 | 7.1207 | -47.2542 | -14.1371 | -1.1888 | -1.1716 |
| 0.1733 | 11.6667 | 875 | 0.2433 | 1.4901 | -5.6244 | 0.6500 | 7.1145 | -47.2326 | -14.1363 | -1.1888 | -1.1716 |
| 0.156 | 12.0 | 900 | 0.2433 | 1.4904 | -5.6265 | 0.6500 | 7.1169 | -47.2397 | -14.1353 | -1.1889 | -1.1717 |
| 0.1906 | 12.3333 | 925 | 0.2433 | 1.4895 | -5.6198 | 0.6500 | 7.1092 | -47.2172 | -14.1384 | -1.1889 | -1.1717 |
| 0.2426 | 12.6667 | 950 | 0.2432 | 1.4854 | -5.6283 | 0.6500 | 7.1136 | -47.2455 | -14.1520 | -1.1886 | -1.1714 |
| 0.2079 | 13.0 | 975 | 0.2432 | 1.4890 | -5.6246 | 0.6500 | 7.1137 | -47.2334 | -14.1398 | -1.1887 | -1.1714 |
| 0.3119 | 13.3333 | 1000 | 0.2432 | 1.4890 | -5.6246 | 0.6500 | 7.1137 | -47.2334 | -14.1398 | -1.1887 | -1.1714 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.0+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1
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Model tree for tsavage68/UTI2_L3_1000steps_1e6rate_03beta_CSFTDPO
Base model
meta-llama/Meta-Llama-3-8B-Instruct
Finetuned
tsavage68/UTI_L3_1000steps_1e5rate_SFT