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llama_DPO_model_e2

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@@ -18,15 +18,15 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0937
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- - Rewards/chosen: 0.4389
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- - Rewards/rejected: -2.0384
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  - Rewards/accuracies: 1.0
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- - Rewards/margins: 2.4774
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- - Logps/rejected: -205.1940
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- - Logps/chosen: -156.2447
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- - Logits/rejected: -1.0509
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- - Logits/chosen: -0.8587
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  ## Model description
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@@ -45,7 +45,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 8e-07
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  - train_batch_size: 1
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  - eval_batch_size: 1
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  - seed: 42
@@ -53,32 +53,42 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 8
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
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  |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
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- | 0.673 | 0.1 | 25 | 0.6445 | 0.0273 | -0.0740 | 0.9000 | 0.1013 | -185.5491 | -160.3607 | -1.0521 | -0.8545 |
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- | 0.5737 | 0.2 | 50 | 0.5485 | 0.0856 | -0.2335 | 0.9933 | 0.3190 | -187.1442 | -159.7781 | -1.0526 | -0.8551 |
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- | 0.4843 | 0.3 | 75 | 0.4496 | 0.1470 | -0.4343 | 1.0 | 0.5814 | -189.1528 | -159.1637 | -1.0527 | -0.8571 |
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- | 0.4006 | 0.4 | 100 | 0.3655 | 0.2043 | -0.6419 | 1.0 | 0.8462 | -191.2286 | -158.5909 | -1.0521 | -0.8556 |
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- | 0.3417 | 0.5 | 125 | 0.2945 | 0.2551 | -0.8630 | 1.0 | 1.1180 | -193.4393 | -158.0833 | -1.0522 | -0.8562 |
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- | 0.2601 | 0.6 | 150 | 0.2353 | 0.3032 | -1.0903 | 1.0 | 1.3935 | -195.7128 | -157.6020 | -1.0520 | -0.8597 |
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- | 0.2197 | 0.7 | 175 | 0.1891 | 0.3442 | -1.3124 | 1.0 | 1.6565 | -197.9333 | -157.1923 | -1.0522 | -0.8579 |
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- | 0.1675 | 0.79 | 200 | 0.1532 | 0.3815 | -1.5253 | 1.0 | 1.9067 | -200.0621 | -156.8192 | -1.0526 | -0.8582 |
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- | 0.1417 | 0.89 | 225 | 0.1289 | 0.4011 | -1.7082 | 1.0 | 2.1094 | -201.8920 | -156.6225 | -1.0525 | -0.8585 |
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- | 0.1203 | 0.99 | 250 | 0.1117 | 0.4214 | -1.8534 | 1.0 | 2.2748 | -203.3437 | -156.4196 | -1.0517 | -0.8603 |
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- | 0.1156 | 1.09 | 275 | 0.1034 | 0.4296 | -1.9336 | 1.0 | 2.3633 | -204.1459 | -156.3377 | -1.0517 | -0.8590 |
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- | 0.0942 | 1.19 | 300 | 0.0990 | 0.4310 | -1.9823 | 1.0 | 2.4133 | -204.6330 | -156.3240 | -1.0514 | -0.8577 |
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- | 0.0903 | 1.29 | 325 | 0.0957 | 0.4380 | -2.0137 | 1.0 | 2.4517 | -204.9467 | -156.2539 | -1.0511 | -0.8593 |
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- | 0.1023 | 1.39 | 350 | 0.0946 | 0.4384 | -2.0296 | 1.0 | 2.4680 | -205.1059 | -156.2503 | -1.0519 | -0.8587 |
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- | 0.0984 | 1.49 | 375 | 0.0945 | 0.4352 | -2.0350 | 1.0 | 2.4702 | -205.1597 | -156.2819 | -1.0510 | -0.8580 |
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- | 0.0899 | 1.59 | 400 | 0.0939 | 0.4360 | -2.0393 | 1.0 | 2.4752 | -205.2024 | -156.2742 | -1.0513 | -0.8594 |
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- | 0.0883 | 1.69 | 425 | 0.0939 | 0.4374 | -2.0378 | 1.0 | 2.4752 | -205.1877 | -156.2598 | -1.0514 | -0.8590 |
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- | 0.1011 | 1.79 | 450 | 0.0939 | 0.4368 | -2.0412 | 1.0 | 2.4781 | -205.2217 | -156.2654 | -1.0513 | -0.8583 |
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- | 0.0962 | 1.89 | 475 | 0.0935 | 0.4403 | -2.0395 | 1.0 | 2.4798 | -205.2041 | -156.2308 | -1.0510 | -0.8574 |
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- | 0.0971 | 1.99 | 500 | 0.0937 | 0.4389 | -2.0384 | 1.0 | 2.4774 | -205.1940 | -156.2447 | -1.0509 | -0.8587 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset.
20
  It achieves the following results on the evaluation set:
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+ - Loss: 0.1526
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+ - Rewards/chosen: 0.3611
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+ - Rewards/rejected: -1.5450
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  - Rewards/accuracies: 1.0
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+ - Rewards/margins: 1.9061
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+ - Logps/rejected: -200.2592
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+ - Logps/chosen: -157.0226
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+ - Logits/rejected: -1.0513
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+ - Logits/chosen: -0.8571
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-07
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  - train_batch_size: 1
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  - eval_batch_size: 1
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  - seed: 42
 
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  - total_train_batch_size: 8
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
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  |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
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+ | 0.6819 | 0.1 | 25 | 0.6708 | 0.0151 | -0.0312 | 0.7567 | 0.0463 | -185.1220 | -160.4831 | -1.0517 | -0.8540 |
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+ | 0.6351 | 0.2 | 50 | 0.6228 | 0.0428 | -0.1054 | 0.9600 | 0.1482 | -185.8636 | -160.2060 | -1.0524 | -0.8552 |
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+ | 0.5874 | 0.3 | 75 | 0.5655 | 0.0762 | -0.2019 | 0.9967 | 0.2781 | -186.8286 | -159.8719 | -1.0525 | -0.8548 |
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+ | 0.5179 | 0.4 | 100 | 0.5030 | 0.1133 | -0.3207 | 1.0 | 0.4340 | -188.0166 | -159.5010 | -1.0521 | -0.8545 |
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+ | 0.479 | 0.5 | 125 | 0.4468 | 0.1501 | -0.4388 | 1.0 | 0.5889 | -189.1974 | -159.1327 | -1.0524 | -0.8554 |
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+ | 0.406 | 0.6 | 150 | 0.3904 | 0.1842 | -0.5778 | 1.0 | 0.7620 | -190.5874 | -158.7915 | -1.0525 | -0.8576 |
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+ | 0.3731 | 0.7 | 175 | 0.3377 | 0.2223 | -0.7247 | 1.0 | 0.9470 | -192.0564 | -158.4104 | -1.0521 | -0.8559 |
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+ | 0.3075 | 0.79 | 200 | 0.2918 | 0.2537 | -0.8769 | 1.0 | 1.1305 | -193.5782 | -158.0974 | -1.0525 | -0.8583 |
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+ | 0.2621 | 0.89 | 225 | 0.2517 | 0.2822 | -1.0278 | 1.0 | 1.3100 | -195.0876 | -157.8119 | -1.0525 | -0.8573 |
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+ | 0.2285 | 0.99 | 250 | 0.2180 | 0.3118 | -1.1738 | 1.0 | 1.4855 | -196.5471 | -157.5160 | -1.0517 | -0.8568 |
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+ | 0.2162 | 1.09 | 275 | 0.1948 | 0.3279 | -1.2897 | 1.0 | 1.6176 | -197.7066 | -157.3551 | -1.0513 | -0.8567 |
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+ | 0.1752 | 1.19 | 300 | 0.1810 | 0.3383 | -1.3661 | 1.0 | 1.7044 | -198.4706 | -157.2514 | -1.0511 | -0.8576 |
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+ | 0.1672 | 1.29 | 325 | 0.1714 | 0.3456 | -1.4242 | 1.0 | 1.7698 | -199.0516 | -157.1775 | -1.0509 | -0.8568 |
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+ | 0.1722 | 1.39 | 350 | 0.1646 | 0.3535 | -1.4653 | 1.0 | 1.8187 | -199.4624 | -157.0993 | -1.0510 | -0.8568 |
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+ | 0.1649 | 1.49 | 375 | 0.1596 | 0.3586 | -1.4919 | 1.0 | 1.8505 | -199.7286 | -157.0477 | -1.0512 | -0.8569 |
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+ | 0.1534 | 1.59 | 400 | 0.1580 | 0.3603 | -1.5059 | 1.0 | 1.8663 | -199.8687 | -157.0304 | -1.0507 | -0.8571 |
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+ | 0.1492 | 1.69 | 425 | 0.1561 | 0.3589 | -1.5194 | 1.0 | 1.8783 | -200.0034 | -157.0448 | -1.0514 | -0.8578 |
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+ | 0.1625 | 1.79 | 450 | 0.1564 | 0.3586 | -1.5205 | 1.0 | 1.8791 | -200.0150 | -157.0482 | -1.0509 | -0.8570 |
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+ | 0.1561 | 1.89 | 475 | 0.1535 | 0.3613 | -1.5366 | 1.0 | 1.8979 | -200.1756 | -157.0212 | -1.0510 | -0.8576 |
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+ | 0.1565 | 1.99 | 500 | 0.1529 | 0.3643 | -1.5393 | 1.0 | 1.9036 | -200.2028 | -156.9913 | -1.0513 | -0.8567 |
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+ | 0.1476 | 2.09 | 525 | 0.1530 | 0.3640 | -1.5392 | 1.0 | 1.9032 | -200.2021 | -156.9944 | -1.0511 | -0.8569 |
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+ | 0.1457 | 2.19 | 550 | 0.1530 | 0.3605 | -1.5406 | 1.0 | 1.9011 | -200.2155 | -157.0287 | -1.0507 | -0.8577 |
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+ | 0.1376 | 2.29 | 575 | 0.1529 | 0.3585 | -1.5466 | 1.0 | 1.9051 | -200.2757 | -157.0492 | -1.0508 | -0.8579 |
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+ | 0.1574 | 2.38 | 600 | 0.1527 | 0.3634 | -1.5448 | 1.0 | 1.9082 | -200.2574 | -156.9998 | -1.0508 | -0.8566 |
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+ | 0.1662 | 2.48 | 625 | 0.1518 | 0.3645 | -1.5465 | 1.0 | 1.9109 | -200.2742 | -156.9890 | -1.0509 | -0.8572 |
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+ | 0.1535 | 2.58 | 650 | 0.1523 | 0.3628 | -1.5458 | 1.0 | 1.9086 | -200.2675 | -157.0059 | -1.0510 | -0.8571 |
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+ | 0.1488 | 2.68 | 675 | 0.1518 | 0.3658 | -1.5446 | 1.0 | 1.9104 | -200.2561 | -156.9763 | -1.0510 | -0.8572 |
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+ | 0.1564 | 2.78 | 700 | 0.1526 | 0.3618 | -1.5452 | 1.0 | 1.9071 | -200.2618 | -157.0154 | -1.0512 | -0.8568 |
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+ | 0.1367 | 2.88 | 725 | 0.1526 | 0.3643 | -1.5426 | 1.0 | 1.9069 | -200.2352 | -156.9905 | -1.0513 | -0.8570 |
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+ | 0.1543 | 2.98 | 750 | 0.1526 | 0.3611 | -1.5450 | 1.0 | 1.9061 | -200.2592 | -157.0226 | -1.0513 | -0.8571 |
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  ### Framework versions