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Mojiz-DPO

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  1. README.md +48 -48
  2. adapter_model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,15 +16,15 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [ahmedabdelwahed/Mojiz-sft](https://huggingface.co/ahmedabdelwahed/Mojiz-sft) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0000
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- - Rewards/chosen: 15.1079
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- - Rewards/rejected: -6.5472
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  - Rewards/accuracies: 1.0
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- - Rewards/margins: 21.6551
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- - Logps/rejected: -84.1339
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- - Logps/chosen: -296.0972
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- - Logits/rejected: -11.3999
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- - Logits/chosen: -12.4435
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  ## Model description
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@@ -56,46 +56,46 @@ 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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- | 1.0153 | 0.41 | 100 | 0.2835 | 0.9457 | -0.2302 | 1.0 | 1.1759 | -71.4998 | -324.4215 | -11.7052 | -12.9375 |
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- | 0.5338 | 0.82 | 200 | 0.0112 | 4.5514 | -1.5056 | 1.0 | 6.0570 | -74.0507 | -317.2103 | -11.5975 | -12.7612 |
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- | 0.0842 | 1.22 | 300 | 0.0005 | 7.6511 | -2.9110 | 1.0 | 10.5622 | -76.8615 | -311.0108 | -11.4999 | -12.6020 |
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- | 0.0047 | 1.63 | 400 | 0.0001 | 8.8644 | -3.3376 | 1.0 | 12.2020 | -77.7146 | -308.5843 | -11.4753 | -12.5618 |
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- | 0.0355 | 2.04 | 500 | 0.0000 | 10.2021 | -3.9578 | 1.0 | 14.1600 | -78.9551 | -305.9088 | -11.4429 | -12.5096 |
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- | 0.0016 | 2.45 | 600 | 0.0000 | 10.8002 | -4.1821 | 1.0 | 14.9823 | -79.4036 | -304.7126 | -11.4421 | -12.5066 |
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- | 0.01 | 2.86 | 700 | 0.0000 | 11.4426 | -4.4892 | 1.0 | 15.9318 | -80.0179 | -303.4279 | -11.4209 | -12.4716 |
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- | 0.0004 | 3.27 | 800 | 0.0000 | 12.0164 | -4.7722 | 1.0 | 16.7886 | -80.5838 | -302.2802 | -11.4134 | -12.4612 |
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- | 0.0 | 3.67 | 900 | 0.0000 | 12.3416 | -5.0090 | 1.0 | 17.3506 | -81.0574 | -301.6299 | -11.4002 | -12.4419 |
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- | 0.0 | 4.08 | 1000 | 0.0000 | 12.6213 | -5.1883 | 1.0 | 17.8096 | -81.4161 | -301.0705 | -11.3951 | -12.4329 |
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- | 0.0016 | 4.49 | 1100 | 0.0000 | 12.8747 | -5.4492 | 1.0 | 18.3238 | -81.9378 | -300.5637 | -11.3826 | -12.4118 |
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- | 0.0001 | 4.9 | 1200 | 0.0000 | 13.1745 | -5.6413 | 1.0 | 18.8158 | -82.3221 | -299.9641 | -11.3761 | -12.4020 |
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- | 0.0002 | 5.31 | 1300 | 0.0000 | 13.3994 | -5.8027 | 1.0 | 19.2020 | -82.6448 | -299.5143 | -11.3782 | -12.4062 |
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- | 0.0015 | 5.71 | 1400 | 0.0000 | 13.6115 | -5.8539 | 1.0 | 19.4653 | -82.7472 | -299.0901 | -11.3819 | -12.4138 |
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- | 0.0 | 6.12 | 1500 | 0.0000 | 13.7666 | -5.9291 | 1.0 | 19.6957 | -82.8977 | -298.7799 | -11.3783 | -12.4090 |
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- | 0.0043 | 6.53 | 1600 | 0.0000 | 13.9182 | -6.0426 | 1.0 | 19.9608 | -83.1246 | -298.4767 | -11.3829 | -12.4160 |
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- | 0.0001 | 6.94 | 1700 | 0.0000 | 14.0272 | -6.1094 | 1.0 | 20.1366 | -83.2582 | -298.2587 | -11.3822 | -12.4155 |
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- | 0.0004 | 7.35 | 1800 | 0.0000 | 14.0888 | -6.1416 | 1.0 | 20.2304 | -83.3227 | -298.1355 | -11.3821 | -12.4156 |
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- | 0.0004 | 7.76 | 1900 | 0.0000 | 14.2101 | -6.1763 | 1.0 | 20.3864 | -83.3921 | -297.8928 | -11.3858 | -12.4218 |
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- | 0.0 | 8.16 | 2000 | 0.0000 | 14.3226 | -6.1877 | 1.0 | 20.5103 | -83.4148 | -297.6679 | -11.3887 | -12.4270 |
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- | 0.0002 | 8.57 | 2100 | 0.0000 | 14.3466 | -6.2002 | 1.0 | 20.5468 | -83.4399 | -297.6199 | -11.3885 | -12.4269 |
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- | 0.0 | 8.98 | 2200 | 0.0000 | 14.3872 | -6.2212 | 1.0 | 20.6084 | -83.4819 | -297.5387 | -11.3885 | -12.4257 |
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- | 0.0 | 9.39 | 2300 | 0.0000 | 14.5099 | -6.2268 | 1.0 | 20.7367 | -83.4931 | -297.2933 | -11.3916 | -12.4312 |
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- | 0.0 | 9.8 | 2400 | 0.0000 | 14.5304 | -6.2424 | 1.0 | 20.7728 | -83.5242 | -297.2522 | -11.3914 | -12.4308 |
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- | 0.0015 | 10.2 | 2500 | 0.0000 | 14.6116 | -6.2599 | 1.0 | 20.8715 | -83.5592 | -297.0899 | -11.3938 | -12.4342 |
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- | 0.0001 | 10.61 | 2600 | 0.0000 | 14.7078 | -6.2887 | 1.0 | 20.9965 | -83.6168 | -296.8975 | -11.3985 | -12.4420 |
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- | 0.0004 | 11.02 | 2700 | 0.0000 | 14.7333 | -6.3343 | 1.0 | 21.0677 | -83.7081 | -296.8464 | -11.3973 | -12.4400 |
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- | 0.0 | 11.43 | 2800 | 0.0000 | 14.7861 | -6.3400 | 1.0 | 21.1261 | -83.7195 | -296.7409 | -11.4011 | -12.4455 |
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- | 0.0001 | 11.84 | 2900 | 0.0000 | 14.8789 | -6.3449 | 1.0 | 21.2238 | -83.7293 | -296.5553 | -11.4036 | -12.4488 |
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- | 0.0 | 12.24 | 3000 | 0.0000 | 14.8969 | -6.3595 | 1.0 | 21.2564 | -83.7584 | -296.5193 | -11.4030 | -12.4480 |
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- | 0.0002 | 12.65 | 3100 | 0.0000 | 14.9154 | -6.3623 | 1.0 | 21.2778 | -83.7641 | -296.4821 | -11.4050 | -12.4512 |
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- | 0.0 | 13.06 | 3200 | 0.0000 | 14.9816 | -6.4106 | 1.0 | 21.3921 | -83.8606 | -296.3499 | -11.4030 | -12.4480 |
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- | 0.0002 | 13.47 | 3300 | 0.0000 | 15.0112 | -6.4324 | 1.0 | 21.4435 | -83.9042 | -296.2907 | -11.4026 | -12.4480 |
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- | 0.0002 | 13.88 | 3400 | 0.0000 | 15.0257 | -6.4814 | 1.0 | 21.5071 | -84.0022 | -296.2616 | -11.4002 | -12.4437 |
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- | 0.0 | 14.29 | 3500 | 0.0000 | 15.0299 | -6.4864 | 1.0 | 21.5163 | -84.0123 | -296.2532 | -11.4000 | -12.4433 |
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- | 0.0 | 14.69 | 3600 | 0.0000 | 15.0596 | -6.5040 | 1.0 | 21.5637 | -84.0475 | -296.1938 | -11.4008 | -12.4445 |
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- | 0.0002 | 15.1 | 3700 | 0.0000 | 15.0792 | -6.5295 | 1.0 | 21.6087 | -84.0985 | -296.1547 | -11.3994 | -12.4422 |
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- | 0.0034 | 15.51 | 3800 | 0.0000 | 15.0977 | -6.5395 | 1.0 | 21.6372 | -84.1184 | -296.1176 | -11.4000 | -12.4437 |
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- | 0.0005 | 15.92 | 3900 | 0.0000 | 15.1032 | -6.5439 | 1.0 | 21.6471 | -84.1273 | -296.1067 | -11.3998 | -12.4433 |
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- | 0.0002 | 16.33 | 4000 | 0.0000 | 15.1079 | -6.5472 | 1.0 | 21.6551 | -84.1339 | -296.0972 | -11.3999 | -12.4435 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [ahmedabdelwahed/Mojiz-sft](https://huggingface.co/ahmedabdelwahed/Mojiz-sft) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0004
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+ - Rewards/chosen: 4.9321
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+ - Rewards/rejected: -3.1907
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  - Rewards/accuracies: 1.0
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+ - Rewards/margins: 8.1228
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+ - Logps/rejected: -102.9468
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+ - Logps/chosen: -276.9925
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+ - Logits/rejected: -11.5352
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+ - Logits/chosen: -12.8189
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  ## Model description
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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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+ | 0.59 | 0.41 | 100 | 0.5689 | 0.2142 | -0.0529 | 1.0 | 0.2670 | -71.5682 | -324.1714 | -11.7019 | -12.9321 |
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+ | 0.3343 | 0.82 | 200 | 0.2046 | 1.1503 | -0.4195 | 1.0 | 1.5698 | -75.2343 | -314.8096 | -11.5589 | -12.6981 |
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+ | 0.1352 | 1.22 | 300 | 0.0544 | 2.1788 | -0.9611 | 1.0 | 3.1399 | -80.6501 | -304.5251 | -11.3938 | -12.4321 |
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+ | 0.0394 | 1.63 | 400 | 0.0235 | 2.7263 | -1.2443 | 1.0 | 3.9706 | -83.4828 | -299.0500 | -11.3316 | -12.3395 |
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+ | 0.0406 | 2.04 | 500 | 0.0129 | 3.0958 | -1.4814 | 1.0 | 4.5771 | -85.8533 | -295.3555 | -11.2949 | -12.2909 |
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+ | 0.0288 | 2.45 | 600 | 0.0085 | 3.3507 | -1.6368 | 1.0 | 4.9875 | -87.4073 | -292.8057 | -11.2931 | -12.2987 |
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+ | 0.0168 | 2.86 | 700 | 0.0058 | 3.5726 | -1.7858 | 1.0 | 5.3584 | -88.8972 | -290.5872 | -11.2839 | -12.2960 |
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+ | 0.0124 | 3.27 | 800 | 0.0044 | 3.7498 | -1.8907 | 1.0 | 5.6405 | -89.9465 | -288.8147 | -11.2953 | -12.3275 |
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+ | 0.0087 | 3.67 | 900 | 0.0035 | 3.8535 | -2.0148 | 1.0 | 5.8684 | -91.1878 | -287.7778 | -11.2906 | -12.3302 |
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+ | 0.007 | 4.08 | 1000 | 0.0029 | 3.9744 | -2.0910 | 1.0 | 6.0654 | -91.9495 | -286.5689 | -11.3025 | -12.3602 |
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+ | 0.0122 | 4.49 | 1100 | 0.0023 | 4.0733 | -2.1965 | 1.0 | 6.2698 | -93.0046 | -285.5799 | -11.3092 | -12.3815 |
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+ | 0.0062 | 4.9 | 1200 | 0.0020 | 4.1431 | -2.2995 | 1.0 | 6.4426 | -94.0349 | -284.8822 | -11.3084 | -12.3870 |
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+ | 0.0113 | 5.31 | 1300 | 0.0017 | 4.2353 | -2.3425 | 1.0 | 6.5778 | -94.4643 | -283.9596 | -11.3304 | -12.4328 |
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+ | 0.0096 | 5.71 | 1400 | 0.0015 | 4.3008 | -2.4035 | 1.0 | 6.7044 | -95.0748 | -283.3046 | -11.3438 | -12.4598 |
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+ | 0.0054 | 6.12 | 1500 | 0.0013 | 4.3515 | -2.4735 | 1.0 | 6.8250 | -95.7742 | -282.7977 | -11.3476 | -12.4711 |
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+ | 0.0127 | 6.53 | 1600 | 0.0012 | 4.4101 | -2.5237 | 1.0 | 6.9338 | -96.2767 | -282.2122 | -11.3609 | -12.4973 |
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+ | 0.0046 | 6.94 | 1700 | 0.0011 | 4.4473 | -2.5927 | 1.0 | 7.0400 | -96.9663 | -281.8404 | -11.3694 | -12.5148 |
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+ | 0.0049 | 7.35 | 1800 | 0.0010 | 4.4882 | -2.6539 | 1.0 | 7.1421 | -97.5784 | -281.4307 | -11.3787 | -12.5361 |
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+ | 0.0039 | 7.76 | 1900 | 0.0009 | 4.5274 | -2.7045 | 1.0 | 7.2319 | -98.0843 | -281.0386 | -11.3905 | -12.5571 |
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+ | 0.0044 | 8.16 | 2000 | 0.0008 | 4.5889 | -2.7282 | 1.0 | 7.3171 | -98.3214 | -280.4241 | -11.4088 | -12.5904 |
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+ | 0.0065 | 8.57 | 2100 | 0.0008 | 4.6306 | -2.7613 | 1.0 | 7.3919 | -98.6527 | -280.0075 | -11.4171 | -12.6086 |
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+ | 0.0033 | 8.98 | 2200 | 0.0007 | 4.6508 | -2.8105 | 1.0 | 7.4613 | -99.1442 | -279.8048 | -11.4214 | -12.6158 |
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+ | 0.0041 | 9.39 | 2300 | 0.0007 | 4.6876 | -2.8441 | 1.0 | 7.5316 | -99.4804 | -279.4375 | -11.4311 | -12.6356 |
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+ | 0.0025 | 9.8 | 2400 | 0.0006 | 4.7079 | -2.8946 | 1.0 | 7.6026 | -99.9857 | -279.2337 | -11.4363 | -12.6466 |
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+ | 0.0113 | 10.2 | 2500 | 0.0006 | 4.7531 | -2.9135 | 1.0 | 7.6665 | -100.1742 | -278.7823 | -11.4524 | -12.6747 |
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+ | 0.004 | 10.61 | 2600 | 0.0006 | 4.7825 | -2.9382 | 1.0 | 7.7207 | -100.4218 | -278.4879 | -11.4644 | -12.6965 |
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+ | 0.0035 | 11.02 | 2700 | 0.0005 | 4.7952 | -2.9793 | 1.0 | 7.7745 | -100.8324 | -278.3613 | -11.4722 | -12.7103 |
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+ | 0.0018 | 11.43 | 2800 | 0.0005 | 4.8215 | -3.0007 | 1.0 | 7.8222 | -101.0460 | -278.0980 | -11.4836 | -12.7306 |
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+ | 0.0036 | 11.84 | 2900 | 0.0005 | 4.8430 | -3.0254 | 1.0 | 7.8684 | -101.2935 | -277.8831 | -11.4928 | -12.7447 |
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+ | 0.0015 | 12.24 | 3000 | 0.0005 | 4.8521 | -3.0583 | 1.0 | 7.9104 | -101.6220 | -277.7916 | -11.4961 | -12.7505 |
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+ | 0.0052 | 12.65 | 3100 | 0.0005 | 4.8654 | -3.0809 | 1.0 | 7.9463 | -101.8486 | -277.6590 | -11.5056 | -12.7670 |
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+ | 0.0022 | 13.06 | 3200 | 0.0005 | 4.8844 | -3.0964 | 1.0 | 7.9807 | -102.0031 | -277.4695 | -11.5118 | -12.7789 |
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+ | 0.002 | 13.47 | 3300 | 0.0004 | 4.8951 | -3.1182 | 1.0 | 8.0133 | -102.2215 | -277.3618 | -11.5162 | -12.7874 |
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+ | 0.0022 | 13.88 | 3400 | 0.0004 | 4.9070 | -3.1334 | 1.0 | 8.0404 | -102.3737 | -277.2430 | -11.5216 | -12.7971 |
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+ | 0.0021 | 14.29 | 3500 | 0.0004 | 4.9110 | -3.1522 | 1.0 | 8.0632 | -102.5618 | -277.2032 | -11.5242 | -12.8018 |
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+ | 0.0016 | 14.69 | 3600 | 0.0004 | 4.9225 | -3.1606 | 1.0 | 8.0831 | -102.6452 | -277.0878 | -11.5305 | -12.8112 |
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+ | 0.0038 | 15.1 | 3700 | 0.0004 | 4.9251 | -3.1769 | 1.0 | 8.1020 | -102.8086 | -277.0620 | -11.5312 | -12.8121 |
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+ | 0.0081 | 15.51 | 3800 | 0.0004 | 4.9290 | -3.1834 | 1.0 | 8.1124 | -102.8736 | -277.0229 | -11.5335 | -12.8159 |
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+ | 0.0021 | 15.92 | 3900 | 0.0004 | 4.9308 | -3.1902 | 1.0 | 8.1210 | -102.9418 | -277.0052 | -11.5346 | -12.8179 |
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+ | 0.0019 | 16.33 | 4000 | 0.0004 | 4.9321 | -3.1907 | 1.0 | 8.1228 | -102.9468 | -276.9925 | -11.5352 | -12.8189 |
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  ### Framework versions
adapter_model.safetensors CHANGED
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