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legal_mistral

PEFT
Safetensors
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@@ -16,27 +16,27 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6841
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- - Law Precision: 0.7927
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- - Law Recall: 0.8784
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- - Law F1: 0.8333
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  - Law Number: 74
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- - Violated by Precision: 0.6593
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- - Violated by Recall: 0.8219
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- - Violated by F1: 0.7317
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  - Violated by Number: 73
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- - Violated on Precision: 0.3919
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- - Violated on Recall: 0.5273
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- - Violated on F1: 0.4496
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  - Violated on Number: 55
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- - Violation Precision: 0.4662
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- - Violation Recall: 0.6190
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- - Violation F1: 0.5318
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  - Violation Number: 601
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- - Overall Precision: 0.5033
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- - Overall Recall: 0.6550
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- - Overall F1: 0.5693
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- - Overall Accuracy: 0.9409
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  ## Model description
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@@ -61,62 +61,22 @@ The following hyperparameters were used during training:
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  - seed: 42
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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: 50
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Law Precision | Law Recall | Law F1 | Law Number | Violated by Precision | Violated by Recall | Violated by F1 | Violated by Number | Violated on Precision | Violated on Recall | Violated on F1 | Violated on Number | Violation Precision | Violation Recall | Violation F1 | Violation Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:-------------:|:----------:|:------:|:----------:|:---------------------:|:------------------:|:--------------:|:------------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:-------------------:|:----------------:|:------------:|:----------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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- | No log | 1.0 | 45 | 0.3496 | 0.2973 | 0.1486 | 0.1982 | 74 | 0.0 | 0.0 | 0.0 | 73 | 0.0 | 0.0 | 0.0 | 55 | 0.1484 | 0.2696 | 0.1914 | 601 | 0.1532 | 0.2154 | 0.1791 | 0.8813 |
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- | No log | 2.0 | 90 | 0.2812 | 0.3594 | 0.6216 | 0.4554 | 74 | 0.4271 | 0.5616 | 0.4852 | 73 | 0.1538 | 0.1091 | 0.1277 | 55 | 0.2941 | 0.4243 | 0.3474 | 601 | 0.3080 | 0.4334 | 0.3601 | 0.9133 |
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- | No log | 3.0 | 135 | 0.2398 | 0.5536 | 0.8378 | 0.6667 | 74 | 0.4234 | 0.7945 | 0.5524 | 73 | 0.1405 | 0.3091 | 0.1932 | 55 | 0.3086 | 0.4992 | 0.3814 | 601 | 0.3256 | 0.5442 | 0.4075 | 0.9234 |
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- | No log | 4.0 | 180 | 0.2495 | 0.6667 | 0.5676 | 0.6131 | 74 | 0.5672 | 0.5205 | 0.5429 | 73 | 0.2286 | 0.1455 | 0.1778 | 55 | 0.4 | 0.5391 | 0.4592 | 601 | 0.4226 | 0.5131 | 0.4634 | 0.9320 |
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- | No log | 5.0 | 225 | 0.2947 | 0.66 | 0.8919 | 0.7586 | 74 | 0.4627 | 0.8493 | 0.5990 | 73 | 0.3011 | 0.5091 | 0.3784 | 55 | 0.3602 | 0.5724 | 0.4422 | 601 | 0.3900 | 0.6227 | 0.4796 | 0.9286 |
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- | No log | 6.0 | 270 | 0.3395 | 0.8026 | 0.8243 | 0.8133 | 74 | 0.5833 | 0.8630 | 0.6961 | 73 | 0.2584 | 0.4182 | 0.3194 | 55 | 0.4035 | 0.5774 | 0.4750 | 601 | 0.4360 | 0.6152 | 0.5103 | 0.9352 |
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- | No log | 7.0 | 315 | 0.3844 | 0.4793 | 0.7838 | 0.5949 | 74 | 0.4122 | 0.8356 | 0.5520 | 73 | 0.3165 | 0.4545 | 0.3731 | 55 | 0.3769 | 0.5757 | 0.4556 | 601 | 0.3870 | 0.6102 | 0.4737 | 0.9336 |
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- | No log | 8.0 | 360 | 0.3227 | 0.6854 | 0.8243 | 0.7485 | 74 | 0.5424 | 0.8767 | 0.6702 | 73 | 0.2385 | 0.4727 | 0.3171 | 55 | 0.4169 | 0.6007 | 0.4922 | 601 | 0.4332 | 0.6376 | 0.5159 | 0.9380 |
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- | No log | 9.0 | 405 | 0.5972 | 0.8205 | 0.8649 | 0.8421 | 74 | 0.6145 | 0.6986 | 0.6538 | 73 | 0.3548 | 0.4 | 0.3761 | 55 | 0.3922 | 0.6506 | 0.4894 | 601 | 0.4328 | 0.6575 | 0.5220 | 0.9258 |
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- | No log | 10.0 | 450 | 0.4920 | 0.6630 | 0.8243 | 0.7349 | 74 | 0.6465 | 0.8767 | 0.7442 | 73 | 0.3636 | 0.5091 | 0.4242 | 55 | 0.4229 | 0.5524 | 0.4791 | 601 | 0.4606 | 0.6040 | 0.5226 | 0.9357 |
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- | No log | 11.0 | 495 | 0.4504 | 0.7625 | 0.8243 | 0.7922 | 74 | 0.7093 | 0.8356 | 0.7673 | 73 | 0.5085 | 0.5455 | 0.5263 | 55 | 0.4569 | 0.6173 | 0.5251 | 601 | 0.5043 | 0.6513 | 0.5685 | 0.9386 |
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- | 0.254 | 12.0 | 540 | 0.6719 | 0.7356 | 0.8649 | 0.7950 | 74 | 0.625 | 0.8219 | 0.7101 | 73 | 0.4265 | 0.5273 | 0.4715 | 55 | 0.4284 | 0.6323 | 0.5108 | 601 | 0.4684 | 0.6638 | 0.5492 | 0.9336 |
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- | 0.254 | 13.0 | 585 | 0.4562 | 0.7241 | 0.8514 | 0.7826 | 74 | 0.5299 | 0.8493 | 0.6526 | 73 | 0.3973 | 0.5273 | 0.4531 | 55 | 0.4171 | 0.5691 | 0.4814 | 601 | 0.4521 | 0.6177 | 0.5221 | 0.9364 |
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- | 0.254 | 14.0 | 630 | 0.5342 | 0.7765 | 0.8919 | 0.8302 | 74 | 0.7284 | 0.8082 | 0.7662 | 73 | 0.4308 | 0.5091 | 0.4667 | 55 | 0.4410 | 0.6156 | 0.5139 | 601 | 0.4888 | 0.6513 | 0.5585 | 0.9393 |
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- | 0.254 | 15.0 | 675 | 0.5533 | 0.8158 | 0.8378 | 0.8267 | 74 | 0.6835 | 0.7397 | 0.7105 | 73 | 0.3594 | 0.4182 | 0.3866 | 55 | 0.4348 | 0.5990 | 0.5038 | 601 | 0.4766 | 0.6214 | 0.5395 | 0.9388 |
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- | 0.254 | 16.0 | 720 | 0.5893 | 0.7191 | 0.8649 | 0.7853 | 74 | 0.6977 | 0.8219 | 0.7547 | 73 | 0.3571 | 0.4545 | 0.4 | 55 | 0.4411 | 0.6106 | 0.5122 | 601 | 0.4791 | 0.6426 | 0.5489 | 0.9394 |
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- | 0.254 | 17.0 | 765 | 0.5400 | 0.8182 | 0.8514 | 0.8344 | 74 | 0.7089 | 0.7671 | 0.7368 | 73 | 0.3448 | 0.3636 | 0.3540 | 55 | 0.4509 | 0.6106 | 0.5187 | 601 | 0.4922 | 0.6301 | 0.5527 | 0.9409 |
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- | 0.254 | 18.0 | 810 | 0.6109 | 0.7033 | 0.8649 | 0.7758 | 74 | 0.6778 | 0.8356 | 0.7485 | 73 | 0.4462 | 0.5273 | 0.4833 | 55 | 0.4399 | 0.6090 | 0.5108 | 601 | 0.4824 | 0.6476 | 0.5529 | 0.9395 |
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- | 0.254 | 19.0 | 855 | 0.5980 | 0.8442 | 0.8784 | 0.8609 | 74 | 0.6867 | 0.7808 | 0.7308 | 73 | 0.3538 | 0.4182 | 0.3833 | 55 | 0.4530 | 0.6090 | 0.5195 | 601 | 0.4947 | 0.6364 | 0.5566 | 0.9406 |
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- | 0.254 | 20.0 | 900 | 0.6257 | 0.7711 | 0.8649 | 0.8153 | 74 | 0.6593 | 0.8219 | 0.7317 | 73 | 0.3247 | 0.4545 | 0.3788 | 55 | 0.4466 | 0.6190 | 0.5188 | 601 | 0.4806 | 0.6488 | 0.5522 | 0.9397 |
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- | 0.254 | 21.0 | 945 | 0.6424 | 0.8077 | 0.8514 | 0.8289 | 74 | 0.6829 | 0.7671 | 0.7226 | 73 | 0.4694 | 0.4182 | 0.4423 | 55 | 0.4543 | 0.6123 | 0.5216 | 601 | 0.5005 | 0.6351 | 0.5598 | 0.9402 |
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- | 0.254 | 22.0 | 990 | 0.6328 | 0.7442 | 0.8649 | 0.8 | 74 | 0.7024 | 0.8082 | 0.7516 | 73 | 0.4032 | 0.4545 | 0.4274 | 55 | 0.4465 | 0.6173 | 0.5182 | 601 | 0.4882 | 0.6463 | 0.5563 | 0.9389 |
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- | 0.0035 | 23.0 | 1035 | 0.5990 | 0.7529 | 0.8649 | 0.8050 | 74 | 0.6988 | 0.7945 | 0.7436 | 73 | 0.3580 | 0.5273 | 0.4265 | 55 | 0.4352 | 0.6256 | 0.5133 | 601 | 0.4735 | 0.6563 | 0.5501 | 0.9371 |
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- | 0.0035 | 24.0 | 1080 | 0.5796 | 0.8228 | 0.8784 | 0.8497 | 74 | 0.7011 | 0.8356 | 0.7625 | 73 | 0.4054 | 0.5455 | 0.4651 | 55 | 0.4665 | 0.6140 | 0.5302 | 601 | 0.5092 | 0.6538 | 0.5725 | 0.9408 |
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- | 0.0035 | 25.0 | 1125 | 0.6002 | 0.8125 | 0.8784 | 0.8442 | 74 | 0.7143 | 0.8219 | 0.7643 | 73 | 0.4058 | 0.5091 | 0.4516 | 55 | 0.4672 | 0.6273 | 0.5355 | 601 | 0.5096 | 0.6600 | 0.5751 | 0.9410 |
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- | 0.0035 | 26.0 | 1170 | 0.5872 | 0.7927 | 0.8784 | 0.8333 | 74 | 0.7024 | 0.8082 | 0.7516 | 73 | 0.3919 | 0.5273 | 0.4496 | 55 | 0.4608 | 0.6156 | 0.5271 | 601 | 0.5014 | 0.6513 | 0.5666 | 0.9407 |
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- | 0.0035 | 27.0 | 1215 | 0.6015 | 0.8025 | 0.8784 | 0.8387 | 74 | 0.7108 | 0.8082 | 0.7564 | 73 | 0.4154 | 0.4909 | 0.45 | 55 | 0.4538 | 0.6123 | 0.5212 | 601 | 0.4990 | 0.6463 | 0.5632 | 0.9408 |
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- | 0.0035 | 28.0 | 1260 | 0.6268 | 0.8049 | 0.8919 | 0.8462 | 74 | 0.7059 | 0.8219 | 0.7595 | 73 | 0.4110 | 0.5455 | 0.4688 | 55 | 0.4641 | 0.6240 | 0.5323 | 601 | 0.5067 | 0.6613 | 0.5737 | 0.9410 |
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- | 0.0035 | 29.0 | 1305 | 0.6410 | 0.8049 | 0.8919 | 0.8462 | 74 | 0.7143 | 0.8219 | 0.7643 | 73 | 0.4085 | 0.5273 | 0.4603 | 55 | 0.4682 | 0.6240 | 0.5350 | 601 | 0.5106 | 0.6600 | 0.5758 | 0.9412 |
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- | 0.0035 | 30.0 | 1350 | 0.6460 | 0.7976 | 0.9054 | 0.8481 | 74 | 0.6383 | 0.8219 | 0.7186 | 73 | 0.3816 | 0.5273 | 0.4427 | 55 | 0.4478 | 0.6206 | 0.5202 | 601 | 0.4867 | 0.6588 | 0.5598 | 0.9395 |
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- | 0.0035 | 31.0 | 1395 | 0.6601 | 0.7952 | 0.8919 | 0.8408 | 74 | 0.6742 | 0.8219 | 0.7407 | 73 | 0.3827 | 0.5636 | 0.4559 | 55 | 0.4412 | 0.5990 | 0.5081 | 601 | 0.4836 | 0.6438 | 0.5524 | 0.9387 |
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- | 0.0035 | 32.0 | 1440 | 0.6641 | 0.8025 | 0.8784 | 0.8387 | 74 | 0.6667 | 0.8219 | 0.7362 | 73 | 0.3827 | 0.5636 | 0.4559 | 55 | 0.4410 | 0.5973 | 0.5074 | 601 | 0.4831 | 0.6413 | 0.5511 | 0.9382 |
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- | 0.0035 | 33.0 | 1485 | 0.6745 | 0.7586 | 0.8919 | 0.8199 | 74 | 0.6667 | 0.8219 | 0.7362 | 73 | 0.3827 | 0.5636 | 0.4559 | 55 | 0.4490 | 0.6073 | 0.5163 | 601 | 0.4874 | 0.6501 | 0.5571 | 0.9393 |
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- | 0.0064 | 34.0 | 1530 | 0.7091 | 0.7805 | 0.8649 | 0.8205 | 74 | 0.6552 | 0.7808 | 0.7125 | 73 | 0.3974 | 0.5636 | 0.4662 | 55 | 0.4606 | 0.6223 | 0.5294 | 601 | 0.4967 | 0.6550 | 0.5650 | 0.9398 |
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- | 0.0064 | 35.0 | 1575 | 0.7150 | 0.7778 | 0.8514 | 0.8129 | 74 | 0.6552 | 0.7808 | 0.7125 | 73 | 0.4133 | 0.5636 | 0.4769 | 55 | 0.4681 | 0.6223 | 0.5343 | 601 | 0.5038 | 0.6538 | 0.5691 | 0.9399 |
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- | 0.0064 | 36.0 | 1620 | 0.7147 | 0.7901 | 0.8649 | 0.8258 | 74 | 0.6477 | 0.7808 | 0.7081 | 73 | 0.3974 | 0.5636 | 0.4662 | 55 | 0.4669 | 0.6223 | 0.5335 | 601 | 0.5019 | 0.6550 | 0.5683 | 0.9401 |
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- | 0.0064 | 37.0 | 1665 | 0.7586 | 0.8356 | 0.8243 | 0.8299 | 74 | 0.6951 | 0.7808 | 0.7355 | 73 | 0.4054 | 0.5455 | 0.4651 | 55 | 0.4705 | 0.6240 | 0.5365 | 601 | 0.5097 | 0.6513 | 0.5719 | 0.9408 |
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- | 0.0064 | 38.0 | 1710 | 0.6612 | 0.8182 | 0.8514 | 0.8344 | 74 | 0.7229 | 0.8219 | 0.7692 | 73 | 0.3846 | 0.5455 | 0.4511 | 55 | 0.4600 | 0.6323 | 0.5326 | 601 | 0.5009 | 0.6638 | 0.5710 | 0.9383 |
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- | 0.0064 | 39.0 | 1755 | 0.6656 | 0.8052 | 0.8378 | 0.8212 | 74 | 0.6667 | 0.7945 | 0.725 | 73 | 0.3816 | 0.5273 | 0.4427 | 55 | 0.4496 | 0.6007 | 0.5142 | 601 | 0.4890 | 0.6351 | 0.5525 | 0.9395 |
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- | 0.0064 | 40.0 | 1800 | 0.7028 | 0.8 | 0.8649 | 0.8312 | 74 | 0.6932 | 0.8356 | 0.7578 | 73 | 0.3671 | 0.5273 | 0.4328 | 55 | 0.4507 | 0.6389 | 0.5286 | 601 | 0.4895 | 0.6700 | 0.5657 | 0.9373 |
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- | 0.0064 | 41.0 | 1845 | 0.6765 | 0.8205 | 0.8649 | 0.8421 | 74 | 0.6977 | 0.8219 | 0.7547 | 73 | 0.3671 | 0.5273 | 0.4328 | 55 | 0.4537 | 0.5957 | 0.5151 | 601 | 0.4952 | 0.6364 | 0.5569 | 0.9396 |
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- | 0.0064 | 42.0 | 1890 | 0.6769 | 0.8205 | 0.8649 | 0.8421 | 74 | 0.6824 | 0.7945 | 0.7342 | 73 | 0.3919 | 0.5273 | 0.4496 | 55 | 0.4652 | 0.6123 | 0.5287 | 601 | 0.5049 | 0.6463 | 0.5669 | 0.9410 |
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- | 0.0064 | 43.0 | 1935 | 0.6826 | 0.8205 | 0.8649 | 0.8421 | 74 | 0.6941 | 0.8082 | 0.7468 | 73 | 0.3590 | 0.5091 | 0.4211 | 55 | 0.4696 | 0.6173 | 0.5334 | 601 | 0.5063 | 0.6501 | 0.5692 | 0.9410 |
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- | 0.0064 | 44.0 | 1980 | 0.6828 | 0.8205 | 0.8649 | 0.8421 | 74 | 0.6824 | 0.7945 | 0.7342 | 73 | 0.3733 | 0.5091 | 0.4308 | 55 | 0.4662 | 0.6190 | 0.5318 | 601 | 0.5039 | 0.6501 | 0.5677 | 0.9411 |
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- | 0.0013 | 45.0 | 2025 | 0.6757 | 0.8125 | 0.8784 | 0.8442 | 74 | 0.6897 | 0.8219 | 0.75 | 73 | 0.3816 | 0.5273 | 0.4427 | 55 | 0.4583 | 0.6306 | 0.5308 | 601 | 0.4981 | 0.6638 | 0.5691 | 0.9405 |
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- | 0.0013 | 46.0 | 2070 | 0.6777 | 0.7901 | 0.8649 | 0.8258 | 74 | 0.6705 | 0.8082 | 0.7329 | 73 | 0.3590 | 0.5091 | 0.4211 | 55 | 0.4612 | 0.6323 | 0.5333 | 601 | 0.4958 | 0.6613 | 0.5667 | 0.9405 |
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- | 0.0013 | 47.0 | 2115 | 0.6801 | 0.8 | 0.8649 | 0.8312 | 74 | 0.6818 | 0.8219 | 0.7453 | 73 | 0.3816 | 0.5273 | 0.4427 | 55 | 0.4590 | 0.6339 | 0.5325 | 601 | 0.4972 | 0.6650 | 0.5690 | 0.9407 |
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- | 0.0013 | 48.0 | 2160 | 0.6828 | 0.7857 | 0.8919 | 0.8354 | 74 | 0.6593 | 0.8219 | 0.7317 | 73 | 0.3896 | 0.5455 | 0.4545 | 55 | 0.4694 | 0.6256 | 0.5364 | 601 | 0.5052 | 0.6625 | 0.5733 | 0.9408 |
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- | 0.0013 | 49.0 | 2205 | 0.6836 | 0.7927 | 0.8784 | 0.8333 | 74 | 0.6593 | 0.8219 | 0.7317 | 73 | 0.3919 | 0.5273 | 0.4496 | 55 | 0.4649 | 0.6173 | 0.5304 | 601 | 0.5024 | 0.6538 | 0.5682 | 0.9410 |
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- | 0.0013 | 50.0 | 2250 | 0.6841 | 0.7927 | 0.8784 | 0.8333 | 74 | 0.6593 | 0.8219 | 0.7317 | 73 | 0.3919 | 0.5273 | 0.4496 | 55 | 0.4662 | 0.6190 | 0.5318 | 601 | 0.5033 | 0.6550 | 0.5693 | 0.9409 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5885
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+ - Law Precision: 0.7159
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+ - Law Recall: 0.8514
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+ - Law F1: 0.7778
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  - Law Number: 74
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+ - Violated by Precision: 0.6020
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+ - Violated by Recall: 0.8082
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+ - Violated by F1: 0.6901
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  - Violated by Number: 73
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+ - Violated on Precision: 0.3485
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+ - Violated on Recall: 0.4182
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+ - Violated on F1: 0.3802
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  - Violated on Number: 55
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+ - Violation Precision: 0.3967
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+ - Violation Recall: 0.5624
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+ - Violation F1: 0.4652
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  - Violation Number: 601
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+ - Overall Precision: 0.4375
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+ - Overall Recall: 0.6015
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+ - Overall F1: 0.5066
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+ - Overall Accuracy: 0.9353
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41
  ## Model description
42
 
 
61
  - seed: 42
62
  - 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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66
  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Law Precision | Law Recall | Law F1 | Law Number | Violated by Precision | Violated by Recall | Violated by F1 | Violated by Number | Violated on Precision | Violated on Recall | Violated on F1 | Violated on Number | Violation Precision | Violation Recall | Violation F1 | Violation Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:-------------:|:----------:|:------:|:----------:|:---------------------:|:------------------:|:--------------:|:------------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:-------------------:|:----------------:|:------------:|:----------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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+ | No log | 1.0 | 45 | 0.3621 | 0.3158 | 0.1622 | 0.2143 | 74 | 0.0 | 0.0 | 0.0 | 73 | 0.0 | 0.0 | 0.0 | 55 | 0.1146 | 0.1980 | 0.1452 | 601 | 0.1217 | 0.1631 | 0.1394 | 0.8798 |
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+ | No log | 2.0 | 90 | 0.2811 | 0.3488 | 0.6081 | 0.4433 | 74 | 0.5375 | 0.5890 | 0.5621 | 73 | 0.1833 | 0.2 | 0.1913 | 55 | 0.2615 | 0.4077 | 0.3186 | 601 | 0.2852 | 0.4284 | 0.3425 | 0.9139 |
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+ | No log | 3.0 | 135 | 0.2343 | 0.7326 | 0.8514 | 0.7875 | 74 | 0.4914 | 0.7808 | 0.6032 | 73 | 0.2024 | 0.3091 | 0.2446 | 55 | 0.3503 | 0.5275 | 0.4210 | 601 | 0.3812 | 0.5654 | 0.4554 | 0.9248 |
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+ | No log | 4.0 | 180 | 0.2560 | 0.7879 | 0.7027 | 0.7429 | 74 | 0.6212 | 0.5616 | 0.5899 | 73 | 0.325 | 0.2364 | 0.2737 | 55 | 0.3945 | 0.5441 | 0.4573 | 601 | 0.4326 | 0.5392 | 0.4800 | 0.9341 |
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+ | No log | 5.0 | 225 | 0.3492 | 0.6889 | 0.8378 | 0.7561 | 74 | 0.5481 | 0.7808 | 0.6441 | 73 | 0.2895 | 0.4 | 0.3359 | 55 | 0.3782 | 0.5191 | 0.4376 | 601 | 0.4137 | 0.5641 | 0.4773 | 0.9280 |
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+ | No log | 6.0 | 270 | 0.3646 | 0.8205 | 0.8649 | 0.8421 | 74 | 0.6628 | 0.7808 | 0.7170 | 73 | 0.4138 | 0.4364 | 0.4248 | 55 | 0.3783 | 0.5874 | 0.4602 | 601 | 0.4312 | 0.6202 | 0.5087 | 0.9332 |
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+ | No log | 7.0 | 315 | 0.4543 | 0.7738 | 0.8784 | 0.8228 | 74 | 0.6304 | 0.7945 | 0.7030 | 73 | 0.2857 | 0.4 | 0.3333 | 55 | 0.3893 | 0.5707 | 0.4629 | 601 | 0.4303 | 0.6077 | 0.5039 | 0.9349 |
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+ | No log | 8.0 | 360 | 0.5118 | 0.6737 | 0.8649 | 0.7574 | 74 | 0.5 | 0.7945 | 0.6138 | 73 | 0.3068 | 0.4909 | 0.3776 | 55 | 0.3607 | 0.5125 | 0.4234 | 601 | 0.3964 | 0.5691 | 0.4673 | 0.9319 |
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+ | No log | 9.0 | 405 | 0.5735 | 0.7033 | 0.8649 | 0.7758 | 74 | 0.6 | 0.7808 | 0.6786 | 73 | 0.3194 | 0.4182 | 0.3622 | 55 | 0.3976 | 0.5557 | 0.4636 | 601 | 0.4353 | 0.5953 | 0.5029 | 0.9349 |
79
+ | No log | 10.0 | 450 | 0.5885 | 0.7159 | 0.8514 | 0.7778 | 74 | 0.6020 | 0.8082 | 0.6901 | 73 | 0.3485 | 0.4182 | 0.3802 | 55 | 0.3967 | 0.5624 | 0.4652 | 601 | 0.4375 | 0.6015 | 0.5066 | 0.9353 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
80
 
81
 
82
  ### Framework versions
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  size 54617130
 
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