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intent_trading

Text Classification
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Safetensors
bert
Generated from Trainer
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  1. README.md +42 -42
  2. model.safetensors +1 -1
  3. runs/May25_22-54-42_Precision-3660/events.out.tfevents.1716641682.Precision-3660.1584143.0 +2 -2
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1788
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- - Accuracy: 0.9590
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  ## Model description
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@@ -49,46 +49,46 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 235 | 1.6327 | 0.6781 |
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- | No log | 2.0 | 470 | 1.0073 | 0.8852 |
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- | 1.7024 | 3.0 | 705 | 0.6035 | 0.9299 |
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- | 1.7024 | 4.0 | 940 | 0.3965 | 0.9323 |
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- | 0.5941 | 5.0 | 1175 | 0.2810 | 0.9534 |
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- | 0.5941 | 6.0 | 1410 | 0.2259 | 0.9531 |
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- | 0.2567 | 7.0 | 1645 | 0.1949 | 0.9531 |
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- | 0.2567 | 8.0 | 1880 | 0.1723 | 0.9566 |
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- | 0.1484 | 9.0 | 2115 | 0.1736 | 0.9558 |
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- | 0.1484 | 10.0 | 2350 | 0.1545 | 0.9558 |
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- | 0.1084 | 11.0 | 2585 | 0.1559 | 0.9568 |
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- | 0.1084 | 12.0 | 2820 | 0.1562 | 0.9536 |
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- | 0.0824 | 13.0 | 3055 | 0.1486 | 0.9560 |
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- | 0.0824 | 14.0 | 3290 | 0.1450 | 0.9560 |
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- | 0.0714 | 15.0 | 3525 | 0.1386 | 0.9568 |
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- | 0.0714 | 16.0 | 3760 | 0.1412 | 0.9600 |
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- | 0.0714 | 17.0 | 3995 | 0.1475 | 0.9563 |
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- | 0.063 | 18.0 | 4230 | 0.1471 | 0.9558 |
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- | 0.063 | 19.0 | 4465 | 0.1517 | 0.9574 |
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- | 0.0529 | 20.0 | 4700 | 0.1535 | 0.9550 |
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- | 0.0529 | 21.0 | 4935 | 0.1494 | 0.9598 |
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- | 0.0504 | 22.0 | 5170 | 0.1661 | 0.9579 |
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- | 0.0504 | 23.0 | 5405 | 0.1548 | 0.9592 |
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- | 0.0453 | 24.0 | 5640 | 0.1584 | 0.9600 |
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- | 0.0453 | 25.0 | 5875 | 0.1601 | 0.9558 |
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- | 0.0395 | 26.0 | 6110 | 0.1511 | 0.9598 |
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- | 0.0395 | 27.0 | 6345 | 0.1655 | 0.9584 |
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- | 0.0375 | 28.0 | 6580 | 0.1614 | 0.9579 |
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- | 0.0375 | 29.0 | 6815 | 0.1534 | 0.9595 |
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- | 0.0332 | 30.0 | 7050 | 0.1757 | 0.9574 |
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- | 0.0332 | 31.0 | 7285 | 0.1701 | 0.9576 |
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- | 0.0324 | 32.0 | 7520 | 0.1635 | 0.9587 |
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- | 0.0324 | 33.0 | 7755 | 0.1721 | 0.9587 |
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- | 0.0324 | 34.0 | 7990 | 0.1742 | 0.9584 |
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- | 0.0294 | 35.0 | 8225 | 0.1798 | 0.9582 |
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- | 0.0294 | 36.0 | 8460 | 0.1812 | 0.9582 |
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- | 0.029 | 37.0 | 8695 | 0.1759 | 0.9590 |
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- | 0.029 | 38.0 | 8930 | 0.1777 | 0.9600 |
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- | 0.028 | 39.0 | 9165 | 0.1782 | 0.9598 |
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- | 0.028 | 40.0 | 9400 | 0.1788 | 0.9590 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1741
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+ - Accuracy: 0.9548
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 227 | 1.5904 | 0.7689 |
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+ | No log | 2.0 | 454 | 1.0086 | 0.8670 |
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+ | 1.6528 | 3.0 | 681 | 0.6706 | 0.9055 |
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+ | 1.6528 | 4.0 | 908 | 0.4376 | 0.9518 |
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+ | 0.6124 | 5.0 | 1135 | 0.2966 | 0.9551 |
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+ | 0.6124 | 6.0 | 1362 | 0.2373 | 0.9504 |
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+ | 0.2536 | 7.0 | 1589 | 0.1967 | 0.9537 |
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+ | 0.2536 | 8.0 | 1816 | 0.1666 | 0.9565 |
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+ | 0.1476 | 9.0 | 2043 | 0.1642 | 0.9543 |
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+ | 0.1476 | 10.0 | 2270 | 0.1570 | 0.9551 |
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+ | 0.1476 | 11.0 | 2497 | 0.1500 | 0.9543 |
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+ | 0.1067 | 12.0 | 2724 | 0.1469 | 0.9548 |
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+ | 0.1067 | 13.0 | 2951 | 0.1458 | 0.9557 |
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+ | 0.0817 | 14.0 | 3178 | 0.1409 | 0.9540 |
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+ | 0.0817 | 15.0 | 3405 | 0.1426 | 0.9595 |
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+ | 0.0709 | 16.0 | 3632 | 0.1418 | 0.9540 |
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+ | 0.0709 | 17.0 | 3859 | 0.1416 | 0.9557 |
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+ | 0.0631 | 18.0 | 4086 | 0.1373 | 0.9581 |
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+ | 0.0631 | 19.0 | 4313 | 0.1458 | 0.9559 |
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+ | 0.0557 | 20.0 | 4540 | 0.1391 | 0.9559 |
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+ | 0.0557 | 21.0 | 4767 | 0.1526 | 0.9518 |
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+ | 0.0557 | 22.0 | 4994 | 0.1511 | 0.9529 |
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+ | 0.0495 | 23.0 | 5221 | 0.1578 | 0.9526 |
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+ | 0.0495 | 24.0 | 5448 | 0.1360 | 0.9568 |
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+ | 0.0443 | 25.0 | 5675 | 0.1451 | 0.9565 |
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+ | 0.0443 | 26.0 | 5902 | 0.1477 | 0.9562 |
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+ | 0.0419 | 27.0 | 6129 | 0.1624 | 0.9540 |
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+ | 0.0419 | 28.0 | 6356 | 0.1659 | 0.9537 |
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+ | 0.0371 | 29.0 | 6583 | 0.1607 | 0.9548 |
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+ | 0.0371 | 30.0 | 6810 | 0.1638 | 0.9543 |
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+ | 0.035 | 31.0 | 7037 | 0.1655 | 0.9529 |
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+ | 0.035 | 32.0 | 7264 | 0.1662 | 0.9562 |
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+ | 0.035 | 33.0 | 7491 | 0.1702 | 0.9532 |
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+ | 0.033 | 34.0 | 7718 | 0.1662 | 0.9562 |
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+ | 0.033 | 35.0 | 7945 | 0.1667 | 0.9532 |
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+ | 0.0309 | 36.0 | 8172 | 0.1794 | 0.9554 |
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+ | 0.0309 | 37.0 | 8399 | 0.1756 | 0.9546 |
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+ | 0.0292 | 38.0 | 8626 | 0.1722 | 0.9559 |
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+ | 0.0292 | 39.0 | 8853 | 0.1706 | 0.9559 |
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+ | 0.0281 | 40.0 | 9080 | 0.1741 | 0.9548 |
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  ### Framework versions
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