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End of training

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README.md CHANGED
@@ -18,18 +18,18 @@ 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-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2150
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- - Rewards/chosen: -0.0603
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- - Rewards/rejected: -0.2557
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  - Rewards/accuracies: 1.0
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- - Rewards/margins: 0.1953
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- - Logps/rejected: -2.5565
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- - Logps/chosen: -0.6032
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- - Logits/rejected: -0.6237
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- - Logits/chosen: -0.5761
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- - Nll Loss: 0.1599
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- - Log Odds Ratio: -0.0986
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- - Log Odds Chosen: 2.6928
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  ## Model description
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@@ -52,11 +52,8 @@ The following hyperparameters were used during training:
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  - train_batch_size: 2
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  - eval_batch_size: 2
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  - seed: 42
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- - distributed_type: multi-GPU
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- - num_devices: 2
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  - gradient_accumulation_steps: 4
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- - total_train_batch_size: 16
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- - total_eval_batch_size: 4
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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: 10
@@ -65,26 +62,48 @@ 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 | Nll Loss | Log Odds Ratio | Log Odds Chosen |
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  |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
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- | 3.2032 | 0.4762 | 5 | 2.3866 | -0.2104 | -0.2405 | 1.0 | 0.0301 | -2.4052 | -2.1040 | 0.3000 | 0.3159 | 2.2400 | -0.5392 | 0.3377 |
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- | 2.0554 | 0.9524 | 10 | 1.7548 | -0.1555 | -0.1881 | 1.0 | 0.0326 | -1.8807 | -1.5549 | -0.2962 | -0.2709 | 1.6079 | -0.5144 | 0.3986 |
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- | 1.4859 | 1.4286 | 15 | 1.2684 | -0.1328 | -0.1714 | 1.0 | 0.0387 | -1.7144 | -1.3277 | -0.6098 | -0.5813 | 1.1271 | -0.4764 | 0.4978 |
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- | 1.0601 | 1.9048 | 20 | 0.9296 | -0.1168 | -0.1595 | 1.0 | 0.0427 | -1.5953 | -1.1684 | -0.5901 | -0.5618 | 0.7913 | -0.4483 | 0.5763 |
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- | 0.7394 | 2.3810 | 25 | 0.6509 | -0.1056 | -0.1530 | 1.0 | 0.0473 | -1.5297 | -1.0565 | -0.5690 | -0.5380 | 0.5131 | -0.4198 | 0.6621 |
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- | 0.4955 | 2.8571 | 30 | 0.4543 | -0.0950 | -0.1470 | 1.0 | 0.0520 | -1.4696 | -0.9498 | -0.4061 | -0.3748 | 0.3250 | -0.3909 | 0.7564 |
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- | 0.303 | 3.3333 | 35 | 0.3624 | -0.0864 | -0.1449 | 1.0 | 0.0585 | -1.4491 | -0.8643 | -0.4525 | -0.4231 | 0.2426 | -0.3584 | 0.8748 |
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- | 0.2989 | 3.8095 | 40 | 0.3240 | -0.0799 | -0.1469 | 1.0 | 0.0670 | -1.4687 | -0.7987 | -0.6479 | -0.6239 | 0.2182 | -0.3223 | 1.0204 |
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- | 0.218 | 4.2857 | 45 | 0.2962 | -0.0746 | -0.1565 | 1.0 | 0.0820 | -1.5652 | -0.7457 | -0.4218 | -0.3928 | 0.1992 | -0.2722 | 1.2439 |
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- | 0.2639 | 4.7619 | 50 | 0.2732 | -0.0703 | -0.1649 | 1.0 | 0.0945 | -1.6489 | -0.7035 | -0.5638 | -0.5293 | 0.1872 | -0.2354 | 1.4329 |
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- | 0.1963 | 5.2381 | 55 | 0.2569 | -0.0683 | -0.1860 | 1.0 | 0.1177 | -1.8598 | -0.6826 | -0.5460 | -0.5026 | 0.1803 | -0.1898 | 1.7281 |
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- | 0.1853 | 5.7143 | 60 | 0.2465 | -0.0659 | -0.1935 | 1.0 | 0.1276 | -1.9351 | -0.6594 | -0.6998 | -0.6580 | 0.1747 | -0.1714 | 1.8682 |
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- | 0.1904 | 6.1905 | 65 | 0.2378 | -0.0643 | -0.2038 | 1.0 | 0.1395 | -2.0377 | -0.6429 | -0.5732 | -0.5271 | 0.1702 | -0.1529 | 2.0218 |
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- | 0.1813 | 6.6667 | 70 | 0.2310 | -0.0632 | -0.2197 | 1.0 | 0.1565 | -2.1970 | -0.6319 | -0.5843 | -0.5359 | 0.1671 | -0.1332 | 2.2275 |
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- | 0.1771 | 7.1429 | 75 | 0.2245 | -0.0620 | -0.2324 | 1.0 | 0.1703 | -2.3239 | -0.6204 | -0.6483 | -0.6007 | 0.1644 | -0.1192 | 2.3961 |
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- | 0.167 | 7.6190 | 80 | 0.2198 | -0.0611 | -0.2431 | 1.0 | 0.1820 | -2.4313 | -0.6114 | -0.7110 | -0.6634 | 0.1621 | -0.1089 | 2.5366 |
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- | 0.1668 | 8.0952 | 85 | 0.2173 | -0.0609 | -0.2520 | 1.0 | 0.1911 | -2.5201 | -0.6090 | -0.6287 | -0.5819 | 0.1614 | -0.1021 | 2.6395 |
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- | 0.1545 | 8.5714 | 90 | 0.2160 | -0.0604 | -0.2536 | 1.0 | 0.1932 | -2.5363 | -0.6043 | -0.6649 | -0.6180 | 0.1604 | -0.1001 | 2.6690 |
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- | 0.1723 | 9.0476 | 95 | 0.2151 | -0.0604 | -0.2545 | 1.0 | 0.1941 | -2.5451 | -0.6037 | -0.6519 | -0.6047 | 0.1600 | -0.0993 | 2.6794 |
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- | 0.1583 | 9.5238 | 100 | 0.2150 | -0.0603 | -0.2557 | 1.0 | 0.1953 | -2.5565 | -0.6032 | -0.6237 | -0.5761 | 0.1599 | -0.0986 | 2.6928 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1307
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+ - Rewards/chosen: -0.0532
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+ - Rewards/rejected: -0.4544
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  - Rewards/accuracies: 1.0
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+ - Rewards/margins: 0.4011
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+ - Logps/rejected: -4.5438
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+ - Logps/chosen: -0.5325
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+ - Logits/rejected: -0.6053
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+ - Logits/chosen: -0.5946
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+ - Nll Loss: 0.1229
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+ - Log Odds Ratio: -0.0243
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+ - Log Odds Chosen: 4.9661
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  ## Model description
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  - train_batch_size: 2
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  - eval_batch_size: 2
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  - seed: 42
 
 
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  - gradient_accumulation_steps: 4
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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: 10
 
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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 | Nll Loss | Log Odds Ratio | Log Odds Chosen |
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  |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
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+ | 3.1838 | 0.2381 | 5 | 2.3687 | -0.2141 | -0.2396 | 0.9000 | 0.0255 | -2.3962 | -2.1413 | 0.1963 | 0.2099 | 2.2996 | -0.5609 | 0.2917 |
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+ | 2.0549 | 0.4762 | 10 | 1.7681 | -0.1667 | -0.1957 | 0.9000 | 0.0290 | -1.9570 | -1.6671 | -0.3938 | -0.3708 | 1.7001 | -0.5337 | 0.3558 |
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+ | 1.52 | 0.7143 | 15 | 1.2706 | -0.1413 | -0.1758 | 1.0 | 0.0345 | -1.7581 | -1.4131 | -0.7370 | -0.7115 | 1.2041 | -0.4984 | 0.4454 |
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+ | 1.0136 | 0.9524 | 20 | 0.8746 | -0.1219 | -0.1611 | 1.0 | 0.0391 | -1.6107 | -1.2194 | -0.7398 | -0.7111 | 0.8093 | -0.4665 | 0.5323 |
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+ | 0.6723 | 1.1905 | 25 | 0.5716 | -0.1086 | -0.1524 | 1.0 | 0.0438 | -1.5241 | -1.0859 | -0.6821 | -0.6474 | 0.5078 | -0.4362 | 0.6192 |
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+ | 0.4086 | 1.4286 | 30 | 0.3851 | -0.0943 | -0.1439 | 1.0 | 0.0496 | -1.4391 | -0.9432 | -0.6528 | -0.6126 | 0.3261 | -0.4003 | 0.7344 |
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+ | 0.2733 | 1.6667 | 35 | 0.3272 | -0.0852 | -0.1441 | 1.0 | 0.0588 | -1.4407 | -0.8524 | -0.6893 | -0.6529 | 0.2740 | -0.3564 | 0.8915 |
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+ | 0.2696 | 1.9048 | 40 | 0.2898 | -0.0800 | -0.1517 | 1.0 | 0.0717 | -1.5166 | -0.7996 | -0.7221 | -0.6878 | 0.2438 | -0.3088 | 1.0816 |
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+ | 0.2171 | 2.1429 | 45 | 0.2581 | -0.0753 | -0.1708 | 1.0 | 0.0955 | -1.7082 | -0.7534 | -0.7685 | -0.7280 | 0.2206 | -0.2432 | 1.4022 |
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+ | 0.2065 | 2.3810 | 50 | 0.2291 | -0.0707 | -0.2048 | 1.0 | 0.1340 | -2.0477 | -0.7073 | -0.8235 | -0.7790 | 0.2000 | -0.1733 | 1.8822 |
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+ | 0.1714 | 2.6190 | 55 | 0.2067 | -0.0678 | -0.2475 | 1.0 | 0.1797 | -2.4753 | -0.6785 | -0.6796 | -0.6324 | 0.1842 | -0.1243 | 2.4141 |
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+ | 0.1603 | 2.8571 | 60 | 0.1899 | -0.0641 | -0.2729 | 1.0 | 0.2088 | -2.7291 | -0.6411 | -0.8208 | -0.7726 | 0.1707 | -0.1012 | 2.7621 |
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+ | 0.1217 | 3.0952 | 65 | 0.1802 | -0.0622 | -0.3110 | 1.0 | 0.2489 | -3.1102 | -0.6216 | -0.7613 | -0.7154 | 0.1639 | -0.0782 | 3.2132 |
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+ | 0.1121 | 3.3333 | 70 | 0.1754 | -0.0619 | -0.3498 | 1.0 | 0.2879 | -3.4979 | -0.6193 | -0.8189 | -0.7850 | 0.1608 | -0.0624 | 3.6277 |
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+ | 0.1207 | 3.5714 | 75 | 0.1683 | -0.0602 | -0.3715 | 1.0 | 0.3113 | -3.7145 | -0.6020 | -0.8539 | -0.8185 | 0.1545 | -0.0534 | 3.9028 |
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+ | 0.1468 | 3.8095 | 80 | 0.1617 | -0.0581 | -0.3716 | 1.0 | 0.3135 | -3.7163 | -0.5811 | -0.8185 | -0.7738 | 0.1485 | -0.0498 | 3.9601 |
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+ | 0.1076 | 4.0476 | 85 | 0.1563 | -0.0581 | -0.4033 | 1.0 | 0.3452 | -4.0326 | -0.5810 | -0.3847 | -0.3661 | 0.1447 | -0.0410 | 4.2887 |
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+ | 0.0976 | 4.2857 | 90 | 0.1527 | -0.0568 | -0.3869 | 1.0 | 0.3301 | -3.8687 | -0.5678 | -0.8869 | -0.8577 | 0.1412 | -0.0428 | 4.1513 |
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+ | 0.1237 | 4.5238 | 95 | 0.1497 | -0.0569 | -0.4033 | 1.0 | 0.3464 | -4.0334 | -0.5690 | -0.7123 | -0.6884 | 0.1388 | -0.0385 | 4.3232 |
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+ | 0.1098 | 4.7619 | 100 | 0.1454 | -0.0561 | -0.4116 | 1.0 | 0.3555 | -4.1158 | -0.5611 | -0.7347 | -0.7134 | 0.1351 | -0.0360 | 4.4282 |
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+ | 0.0781 | 5.0 | 105 | 0.1449 | -0.0567 | -0.4296 | 1.0 | 0.3729 | -4.2958 | -0.5671 | -0.6652 | -0.6537 | 0.1355 | -0.0324 | 4.6010 |
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+ | 0.0986 | 5.2381 | 110 | 0.1419 | -0.0556 | -0.4165 | 1.0 | 0.3608 | -4.1646 | -0.5563 | -0.7521 | -0.7314 | 0.1325 | -0.0340 | 4.4953 |
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+ | 0.0853 | 5.4762 | 115 | 0.1402 | -0.0552 | -0.4216 | 1.0 | 0.3663 | -4.2159 | -0.5524 | -0.6544 | -0.6378 | 0.1309 | -0.0325 | 4.5586 |
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+ | 0.0867 | 5.7143 | 120 | 0.1386 | -0.0547 | -0.4309 | 1.0 | 0.3761 | -4.3088 | -0.5474 | -0.5502 | -0.5379 | 0.1294 | -0.0306 | 4.6712 |
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+ | 0.0829 | 5.9524 | 125 | 0.1355 | -0.0534 | -0.4306 | 1.0 | 0.3772 | -4.3056 | -0.5341 | -0.7163 | -0.6946 | 0.1265 | -0.0295 | 4.7039 |
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+ | 0.0921 | 6.1905 | 130 | 0.1366 | -0.0547 | -0.4466 | 1.0 | 0.3919 | -4.4659 | -0.5474 | -0.6342 | -0.6229 | 0.1282 | -0.0271 | 4.8385 |
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+ | 0.0874 | 6.4286 | 135 | 0.1358 | -0.0549 | -0.4507 | 1.0 | 0.3959 | -4.5075 | -0.5490 | -0.6402 | -0.6263 | 0.1277 | -0.0267 | 4.8754 |
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+ | 0.082 | 6.6667 | 140 | 0.1346 | -0.0541 | -0.4412 | 1.0 | 0.3872 | -4.4123 | -0.5407 | -0.6918 | -0.6770 | 0.1263 | -0.0277 | 4.7993 |
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+ | 0.0858 | 6.9048 | 145 | 0.1343 | -0.0542 | -0.4452 | 1.0 | 0.3910 | -4.4524 | -0.5425 | -0.5903 | -0.5802 | 0.1260 | -0.0270 | 4.8382 |
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+ | 0.0762 | 7.1429 | 150 | 0.1331 | -0.0539 | -0.4483 | 1.0 | 0.3943 | -4.4825 | -0.5392 | -0.6384 | -0.6278 | 0.1249 | -0.0261 | 4.8798 |
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+ | 0.0704 | 7.3810 | 155 | 0.1321 | -0.0536 | -0.4505 | 1.0 | 0.3970 | -4.5053 | -0.5357 | -0.6361 | -0.6260 | 0.1240 | -0.0255 | 4.9141 |
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+ | 0.078 | 7.6190 | 160 | 0.1317 | -0.0535 | -0.4539 | 1.0 | 0.4003 | -4.5386 | -0.5351 | -0.6485 | -0.6381 | 0.1238 | -0.0248 | 4.9509 |
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+ | 0.0771 | 7.8571 | 165 | 0.1315 | -0.0535 | -0.4579 | 1.0 | 0.4043 | -4.5786 | -0.5355 | -0.6204 | -0.6116 | 0.1238 | -0.0242 | 4.9924 |
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+ | 0.0851 | 8.0952 | 170 | 0.1313 | -0.0535 | -0.4566 | 1.0 | 0.4031 | -4.5664 | -0.5355 | -0.6164 | -0.6068 | 0.1235 | -0.0242 | 4.9829 |
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+ | 0.0654 | 8.3333 | 175 | 0.1305 | -0.0531 | -0.4542 | 1.0 | 0.4011 | -4.5422 | -0.5313 | -0.6323 | -0.6206 | 0.1227 | -0.0243 | 4.9685 |
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+ | 0.082 | 8.5714 | 180 | 0.1308 | -0.0532 | -0.4510 | 1.0 | 0.3978 | -4.5101 | -0.5323 | -0.6397 | -0.6294 | 0.1229 | -0.0247 | 4.9322 |
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+ | 0.0724 | 8.8095 | 185 | 0.1306 | -0.0531 | -0.4539 | 1.0 | 0.4008 | -4.5388 | -0.5307 | -0.6082 | -0.5998 | 0.1227 | -0.0243 | 4.9661 |
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+ | 0.0836 | 9.0476 | 190 | 0.1308 | -0.0533 | -0.4551 | 1.0 | 0.4018 | -4.5512 | -0.5333 | -0.5842 | -0.5754 | 0.1231 | -0.0241 | 4.9712 |
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+ | 0.0702 | 9.2857 | 195 | 0.1308 | -0.0533 | -0.4552 | 1.0 | 0.4019 | -4.5521 | -0.5335 | -0.5966 | -0.5894 | 0.1230 | -0.0244 | 4.9728 |
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+ | 0.0726 | 9.5238 | 200 | 0.1307 | -0.0533 | -0.4547 | 1.0 | 0.4013 | -4.5466 | -0.5335 | -0.6151 | -0.6059 | 0.1229 | -0.0243 | 4.9692 |
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+ | 0.0837 | 9.7619 | 205 | 0.1307 | -0.0534 | -0.4554 | 1.0 | 0.4020 | -4.5538 | -0.5338 | -0.6041 | -0.5956 | 0.1229 | -0.0241 | 4.9743 |
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+ | 0.0796 | 10.0 | 210 | 0.1307 | -0.0532 | -0.4544 | 1.0 | 0.4011 | -4.5438 | -0.5325 | -0.6053 | -0.5946 | 0.1229 | -0.0243 | 4.9661 |
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  ### Framework versions
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