UTI2_L3_1000steps_1e7rate_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: 0.2514
- Rewards/chosen: 1.0384
- Rewards/rejected: -2.5887
- Rewards/accuracies: 0.6500
- Rewards/margins: 3.6271
- Logps/rejected: -37.1137
- Logps/chosen: -15.6419
- Logits/rejected: -1.1635
- Logits/chosen: -1.1553
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-07
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6944 | 0.3333 | 25 | 0.6884 | 0.0045 | -0.0054 | 0.3900 | 0.0099 | -28.5027 | -19.0882 | -1.1523 | -1.1488 |
| 0.6816 | 0.6667 | 50 | 0.6751 | 0.0295 | -0.0076 | 0.5600 | 0.0370 | -28.5099 | -19.0051 | -1.1524 | -1.1488 |
| 0.6338 | 1.0 | 75 | 0.6279 | 0.0961 | -0.0432 | 0.6300 | 0.1392 | -28.6285 | -18.7831 | -1.1525 | -1.1488 |
| 0.5045 | 1.3333 | 100 | 0.5423 | 0.2255 | -0.1296 | 0.6400 | 0.3551 | -28.9166 | -18.3516 | -1.1531 | -1.1490 |
| 0.418 | 1.6667 | 125 | 0.4514 | 0.3749 | -0.2772 | 0.6500 | 0.6522 | -29.4088 | -17.8536 | -1.1538 | -1.1494 |
| 0.4462 | 2.0 | 150 | 0.3918 | 0.4758 | -0.4504 | 0.6500 | 0.9261 | -29.9859 | -17.5174 | -1.1550 | -1.1502 |
| 0.3407 | 2.3333 | 175 | 0.3498 | 0.5690 | -0.6230 | 0.6500 | 1.1920 | -30.5612 | -17.2065 | -1.1554 | -1.1504 |
| 0.2843 | 2.6667 | 200 | 0.3196 | 0.6474 | -0.8203 | 0.6500 | 1.4677 | -31.2189 | -16.9454 | -1.1560 | -1.1507 |
| 0.2531 | 3.0 | 225 | 0.2983 | 0.7087 | -1.0237 | 0.6500 | 1.7323 | -31.8969 | -16.7411 | -1.1565 | -1.1508 |
| 0.2528 | 3.3333 | 250 | 0.2847 | 0.7720 | -1.2036 | 0.6500 | 1.9756 | -32.4966 | -16.5300 | -1.1572 | -1.1512 |
| 0.1933 | 3.6667 | 275 | 0.2751 | 0.8130 | -1.3994 | 0.6500 | 2.2124 | -33.1494 | -16.3934 | -1.1582 | -1.1519 |
| 0.2881 | 4.0 | 300 | 0.2685 | 0.8570 | -1.5612 | 0.6500 | 2.4182 | -33.6888 | -16.2466 | -1.1590 | -1.1525 |
| 0.2511 | 4.3333 | 325 | 0.2642 | 0.8844 | -1.7227 | 0.6500 | 2.6071 | -34.2270 | -16.1553 | -1.1598 | -1.1530 |
| 0.1639 | 4.6667 | 350 | 0.2612 | 0.9186 | -1.8702 | 0.6500 | 2.7887 | -34.7186 | -16.0414 | -1.1606 | -1.1536 |
| 0.2312 | 5.0 | 375 | 0.2579 | 0.9429 | -2.0206 | 0.6500 | 2.9635 | -35.2199 | -15.9604 | -1.1613 | -1.1540 |
| 0.2301 | 5.3333 | 400 | 0.2558 | 0.9559 | -2.1492 | 0.6500 | 3.1051 | -35.6486 | -15.9168 | -1.1616 | -1.1542 |
| 0.2289 | 5.6667 | 425 | 0.2549 | 0.9690 | -2.2386 | 0.6500 | 3.2076 | -35.9468 | -15.8733 | -1.1621 | -1.1545 |
| 0.2106 | 6.0 | 450 | 0.2540 | 0.9873 | -2.3044 | 0.6500 | 3.2918 | -36.1660 | -15.8122 | -1.1622 | -1.1545 |
| 0.2794 | 6.3333 | 475 | 0.2538 | 1.0007 | -2.3501 | 0.6500 | 3.3509 | -36.3185 | -15.7675 | -1.1626 | -1.1548 |
| 0.3133 | 6.6667 | 500 | 0.2535 | 0.9979 | -2.3982 | 0.6500 | 3.3960 | -36.4786 | -15.7771 | -1.1627 | -1.1548 |
| 0.2103 | 7.0 | 525 | 0.2528 | 1.0083 | -2.4563 | 0.6500 | 3.4646 | -36.6723 | -15.7423 | -1.1632 | -1.1551 |
| 0.177 | 7.3333 | 550 | 0.2524 | 1.0160 | -2.4923 | 0.6500 | 3.5083 | -36.7923 | -15.7167 | -1.1630 | -1.1549 |
| 0.2615 | 7.6667 | 575 | 0.2523 | 1.0217 | -2.5108 | 0.6500 | 3.5325 | -36.8539 | -15.6977 | -1.1631 | -1.1550 |
| 0.2613 | 8.0 | 600 | 0.2522 | 1.0242 | -2.5323 | 0.6500 | 3.5566 | -36.9258 | -15.6891 | -1.1630 | -1.1548 |
| 0.2269 | 8.3333 | 625 | 0.2518 | 1.0294 | -2.5471 | 0.6500 | 3.5765 | -36.9751 | -15.6721 | -1.1635 | -1.1553 |
| 0.1059 | 8.6667 | 650 | 0.2521 | 1.0271 | -2.5645 | 0.6500 | 3.5915 | -37.0329 | -15.6797 | -1.1636 | -1.1553 |
| 0.2274 | 9.0 | 675 | 0.2516 | 1.0319 | -2.5726 | 0.6500 | 3.6045 | -37.0601 | -15.6638 | -1.1633 | -1.1551 |
| 0.2265 | 9.3333 | 700 | 0.2517 | 1.0299 | -2.5852 | 0.6500 | 3.6151 | -37.1020 | -15.6702 | -1.1635 | -1.1553 |
| 0.2266 | 9.6667 | 725 | 0.2517 | 1.0257 | -2.5906 | 0.6500 | 3.6162 | -37.1199 | -15.6844 | -1.1635 | -1.1552 |
| 0.3151 | 10.0 | 750 | 0.2517 | 1.0347 | -2.5867 | 0.6500 | 3.6214 | -37.1071 | -15.6543 | -1.1633 | -1.1551 |
| 0.2092 | 10.3333 | 775 | 0.2517 | 1.0320 | -2.5944 | 0.6500 | 3.6264 | -37.1328 | -15.6633 | -1.1636 | -1.1553 |
| 0.2267 | 10.6667 | 800 | 0.2513 | 1.0270 | -2.5989 | 0.6500 | 3.6258 | -37.1475 | -15.6801 | -1.1633 | -1.1550 |
| 0.2444 | 11.0 | 825 | 0.2514 | 1.0330 | -2.5924 | 0.6500 | 3.6254 | -37.1261 | -15.6599 | -1.1635 | -1.1553 |
| 0.2957 | 11.3333 | 850 | 0.2516 | 1.0340 | -2.5935 | 0.6500 | 3.6275 | -37.1297 | -15.6566 | -1.1635 | -1.1552 |
| 0.1754 | 11.6667 | 875 | 0.2516 | 1.0332 | -2.5913 | 0.6500 | 3.6245 | -37.1224 | -15.6594 | -1.1634 | -1.1551 |
| 0.1594 | 12.0 | 900 | 0.2515 | 1.0326 | -2.5942 | 0.6500 | 3.6268 | -37.1320 | -15.6612 | -1.1635 | -1.1552 |
| 0.1921 | 12.3333 | 925 | 0.2514 | 1.0378 | -2.5889 | 0.6500 | 3.6266 | -37.1143 | -15.6441 | -1.1635 | -1.1552 |
| 0.2439 | 12.6667 | 950 | 0.2514 | 1.0384 | -2.5887 | 0.6500 | 3.6271 | -37.1137 | -15.6419 | -1.1635 | -1.1553 |
| 0.2099 | 13.0 | 975 | 0.2514 | 1.0384 | -2.5887 | 0.6500 | 3.6271 | -37.1137 | -15.6419 | -1.1635 | -1.1553 |
| 0.313 | 13.3333 | 1000 | 0.2514 | 1.0384 | -2.5887 | 0.6500 | 3.6271 | -37.1137 | -15.6419 | -1.1635 | -1.1553 |
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_1e7rate_03beta_CSFTDPO
Base model
meta-llama/Meta-Llama-3-8B-Instruct
Finetuned
tsavage68/UTI_L3_1000steps_1e5rate_SFT