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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: 0.0037
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- - Rewards/chosen: 0.5612
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- - Rewards/rejected: -5.9460
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  - Rewards/accuracies: 1.0
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- - Rewards/margins: 6.5073
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- - Logps/rejected: -244.2698
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- - Logps/chosen: -155.0214
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- - Logits/rejected: -1.0632
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- - Logits/chosen: -0.8795
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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: 5e-06
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  - train_batch_size: 1
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  - eval_batch_size: 1
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  - seed: 42
@@ -59,26 +59,26 @@ The following hyperparameters were used during training:
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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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- | 0.3693 | 0.1 | 25 | 0.1586 | 0.3906 | -1.4782 | 1.0 | 1.8688 | -199.5915 | -156.7276 | -1.0532 | -0.8639 |
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- | 0.0442 | 0.2 | 50 | 0.0275 | 0.5577 | -3.3969 | 1.0 | 3.9546 | -218.7789 | -155.0573 | -1.0591 | -0.8709 |
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- | 0.0153 | 0.3 | 75 | 0.0123 | 0.5805 | -4.3685 | 1.0 | 4.9490 | -228.4945 | -154.8291 | -1.0641 | -0.8765 |
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- | 0.0098 | 0.4 | 100 | 0.0083 | 0.5880 | -4.8560 | 1.0 | 5.4440 | -233.3696 | -154.7535 | -1.0654 | -0.8801 |
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- | 0.0072 | 0.5 | 125 | 0.0065 | 0.5779 | -5.1733 | 1.0 | 5.7513 | -236.5429 | -154.8546 | -1.0667 | -0.8808 |
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- | 0.0056 | 0.6 | 150 | 0.0058 | 0.5669 | -5.3483 | 1.0 | 5.9152 | -238.2926 | -154.9651 | -1.0674 | -0.8815 |
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- | 0.0059 | 0.7 | 175 | 0.0051 | 0.5733 | -5.4970 | 1.0 | 6.0704 | -239.7797 | -154.9004 | -1.0659 | -0.8820 |
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- | 0.0065 | 0.79 | 200 | 0.0047 | 0.5713 | -5.6304 | 1.0 | 6.2017 | -241.1136 | -154.9210 | -1.0653 | -0.8803 |
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- | 0.0044 | 0.89 | 225 | 0.0043 | 0.5689 | -5.7514 | 1.0 | 6.3203 | -242.3240 | -154.9452 | -1.0650 | -0.8816 |
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- | 0.004 | 0.99 | 250 | 0.0041 | 0.5671 | -5.8118 | 1.0 | 6.3790 | -242.9280 | -154.9625 | -1.0644 | -0.8796 |
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- | 0.0029 | 1.09 | 275 | 0.0040 | 0.5648 | -5.8589 | 1.0 | 6.4237 | -243.3990 | -154.9863 | -1.0633 | -0.8800 |
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- | 0.0035 | 1.19 | 300 | 0.0038 | 0.5658 | -5.8892 | 1.0 | 6.4549 | -243.7013 | -154.9761 | -1.0630 | -0.8785 |
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- | 0.0024 | 1.29 | 325 | 0.0039 | 0.5618 | -5.9044 | 1.0 | 6.4662 | -243.8535 | -155.0163 | -1.0628 | -0.8787 |
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- | 0.0034 | 1.39 | 350 | 0.0038 | 0.5595 | -5.9136 | 1.0 | 6.4731 | -243.9456 | -155.0389 | -1.0632 | -0.8788 |
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- | 0.0029 | 1.49 | 375 | 0.0038 | 0.5601 | -5.9328 | 1.0 | 6.4929 | -244.1375 | -155.0332 | -1.0634 | -0.8792 |
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- | 0.003 | 1.59 | 400 | 0.0038 | 0.5605 | -5.9352 | 1.0 | 6.4957 | -244.1614 | -155.0284 | -1.0632 | -0.8793 |
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- | 0.0021 | 1.69 | 425 | 0.0038 | 0.5593 | -5.9410 | 1.0 | 6.5003 | -244.2199 | -155.0412 | -1.0630 | -0.8792 |
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- | 0.0036 | 1.79 | 450 | 0.0038 | 0.5605 | -5.9408 | 1.0 | 6.5013 | -244.2178 | -155.0292 | -1.0631 | -0.8794 |
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- | 0.0031 | 1.89 | 475 | 0.0038 | 0.5567 | -5.9439 | 1.0 | 6.5006 | -244.2483 | -155.0666 | -1.0634 | -0.8782 |
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- | 0.0032 | 1.99 | 500 | 0.0037 | 0.5612 | -5.9460 | 1.0 | 6.5073 | -244.2698 | -155.0214 | -1.0632 | -0.8795 |
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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.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0572
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+ - Rewards/chosen: 0.4916
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+ - Rewards/rejected: -2.5677
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  - Rewards/accuracies: 1.0
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+ - Rewards/margins: 3.0592
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+ - Logps/rejected: -210.4865
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+ - Logps/chosen: -155.7183
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+ - Logits/rejected: -1.0527
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+ - Logits/chosen: -0.8611
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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: 1e-06
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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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  | 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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+ | 0.6588 | 0.1 | 25 | 0.6197 | 0.0430 | -0.1117 | 0.9633 | 0.1547 | -185.9265 | -160.2034 | -1.0522 | -0.8546 |
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+ | 0.5198 | 0.2 | 50 | 0.4923 | 0.1198 | -0.3424 | 0.9933 | 0.4622 | -188.2335 | -159.4357 | -1.0525 | -0.8554 |
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+ | 0.422 | 0.3 | 75 | 0.3707 | 0.2016 | -0.6277 | 1.0 | 0.8293 | -191.0862 | -158.6175 | -1.0532 | -0.8571 |
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+ | 0.3133 | 0.4 | 100 | 0.2775 | 0.2622 | -0.9287 | 1.0 | 1.1908 | -194.0961 | -158.0122 | -1.0529 | -0.8575 |
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+ | 0.2536 | 0.5 | 125 | 0.2077 | 0.3244 | -1.2160 | 1.0 | 1.5403 | -196.9694 | -157.3904 | -1.0527 | -0.8608 |
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+ | 0.181 | 0.6 | 150 | 0.1559 | 0.3746 | -1.5115 | 1.0 | 1.8860 | -199.9242 | -156.8883 | -1.0534 | -0.8595 |
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+ | 0.1457 | 0.7 | 175 | 0.1203 | 0.4136 | -1.7795 | 1.0 | 2.1931 | -202.6049 | -156.4983 | -1.0534 | -0.8620 |
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+ | 0.1072 | 0.79 | 200 | 0.0950 | 0.4439 | -2.0245 | 1.0 | 2.4684 | -205.0550 | -156.1949 | -1.0532 | -0.8613 |
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+ | 0.0921 | 0.89 | 225 | 0.0792 | 0.4625 | -2.2196 | 1.0 | 2.6821 | -207.0056 | -156.0085 | -1.0535 | -0.8604 |
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+ | 0.0732 | 0.99 | 250 | 0.0694 | 0.4721 | -2.3665 | 1.0 | 2.8387 | -208.4748 | -155.9124 | -1.0530 | -0.8609 |
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+ | 0.0703 | 1.09 | 275 | 0.0636 | 0.4762 | -2.4589 | 1.0 | 2.9351 | -209.3987 | -155.8720 | -1.0527 | -0.8600 |
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+ | 0.0554 | 1.19 | 300 | 0.0606 | 0.4841 | -2.5053 | 1.0 | 2.9894 | -209.8628 | -155.7928 | -1.0528 | -0.8614 |
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+ | 0.0532 | 1.29 | 325 | 0.0592 | 0.4869 | -2.5331 | 1.0 | 3.0200 | -210.1407 | -155.7649 | -1.0527 | -0.8606 |
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+ | 0.061 | 1.39 | 350 | 0.0580 | 0.4912 | -2.5550 | 1.0 | 3.0462 | -210.3595 | -155.7218 | -1.0525 | -0.8611 |
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+ | 0.0612 | 1.49 | 375 | 0.0573 | 0.4930 | -2.5633 | 1.0 | 3.0563 | -210.4424 | -155.7034 | -1.0527 | -0.8613 |
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+ | 0.0539 | 1.59 | 400 | 0.0576 | 0.4921 | -2.5602 | 1.0 | 3.0523 | -210.4118 | -155.7133 | -1.0529 | -0.8596 |
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+ | 0.0517 | 1.69 | 425 | 0.0570 | 0.4917 | -2.5691 | 1.0 | 3.0608 | -210.5005 | -155.7172 | -1.0529 | -0.8602 |
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+ | 0.0627 | 1.79 | 450 | 0.0570 | 0.4938 | -2.5669 | 1.0 | 3.0607 | -210.4783 | -155.6961 | -1.0532 | -0.8608 |
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+ | 0.0575 | 1.89 | 475 | 0.0574 | 0.4911 | -2.5664 | 1.0 | 3.0574 | -210.4731 | -155.7233 | -1.0528 | -0.8612 |
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+ | 0.0578 | 1.99 | 500 | 0.0572 | 0.4916 | -2.5677 | 1.0 | 3.0592 | -210.4865 | -155.7183 | -1.0527 | -0.8611 |
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  ### Framework versions