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llm-selector

Text Classification
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distilbert
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update model card README.md

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@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1267
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- - Accuracy: 0.9689
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  ## Model description
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@@ -48,46 +48,46 @@ 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 | 33 | 1.8804 | 0.2763 |
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- | No log | 2.0 | 66 | 1.8150 | 0.2685 |
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- | No log | 3.0 | 99 | 1.6717 | 0.4008 |
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- | No log | 4.0 | 132 | 1.4675 | 0.5603 |
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- | No log | 5.0 | 165 | 1.4145 | 0.5409 |
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- | No log | 6.0 | 198 | 1.2399 | 0.6148 |
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- | No log | 7.0 | 231 | 1.1285 | 0.6459 |
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- | No log | 8.0 | 264 | 1.1022 | 0.6498 |
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- | No log | 9.0 | 297 | 0.9927 | 0.6848 |
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- | No log | 10.0 | 330 | 0.9647 | 0.6887 |
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- | No log | 11.0 | 363 | 0.8355 | 0.7393 |
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- | No log | 12.0 | 396 | 0.7587 | 0.7665 |
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- | No log | 13.0 | 429 | 0.6906 | 0.7977 |
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- | No log | 14.0 | 462 | 0.6106 | 0.8171 |
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- | No log | 15.0 | 495 | 0.5611 | 0.8405 |
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- | 1.291 | 16.0 | 528 | 0.5530 | 0.8366 |
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- | 1.291 | 17.0 | 561 | 0.4772 | 0.8444 |
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- | 1.291 | 18.0 | 594 | 0.4174 | 0.8949 |
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- | 1.291 | 19.0 | 627 | 0.4149 | 0.8949 |
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- | 1.291 | 20.0 | 660 | 0.3523 | 0.9144 |
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- | 1.291 | 21.0 | 693 | 0.3326 | 0.9222 |
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- | 1.291 | 22.0 | 726 | 0.3094 | 0.9261 |
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- | 1.291 | 23.0 | 759 | 0.2860 | 0.9339 |
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- | 1.291 | 24.0 | 792 | 0.2762 | 0.9455 |
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- | 1.291 | 25.0 | 825 | 0.2470 | 0.9494 |
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- | 1.291 | 26.0 | 858 | 0.2357 | 0.9455 |
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- | 1.291 | 27.0 | 891 | 0.2130 | 0.9533 |
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- | 1.291 | 28.0 | 924 | 0.1944 | 0.9533 |
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- | 1.291 | 29.0 | 957 | 0.1877 | 0.9494 |
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- | 1.291 | 30.0 | 990 | 0.1755 | 0.9650 |
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- | 0.4249 | 31.0 | 1023 | 0.1661 | 0.9689 |
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- | 0.4249 | 32.0 | 1056 | 0.1618 | 0.9650 |
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- | 0.4249 | 33.0 | 1089 | 0.1541 | 0.9650 |
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- | 0.4249 | 34.0 | 1122 | 0.1506 | 0.9689 |
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- | 0.4249 | 35.0 | 1155 | 0.1376 | 0.9689 |
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- | 0.4249 | 36.0 | 1188 | 0.1336 | 0.9728 |
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- | 0.4249 | 37.0 | 1221 | 0.1316 | 0.9728 |
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- | 0.4249 | 38.0 | 1254 | 0.1285 | 0.9728 |
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- | 0.4249 | 39.0 | 1287 | 0.1270 | 0.9689 |
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- | 0.4249 | 40.0 | 1320 | 0.1267 | 0.9689 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9868
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+ - Accuracy: 0.6923
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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 | 29 | 1.9496 | 0.2308 |
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+ | No log | 2.0 | 58 | 1.7509 | 0.2308 |
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+ | No log | 3.0 | 87 | 1.6608 | 0.3462 |
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+ | No log | 4.0 | 116 | 1.3725 | 0.6154 |
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+ | No log | 5.0 | 145 | 1.3401 | 0.5 |
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+ | No log | 6.0 | 174 | 1.1971 | 0.5385 |
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+ | No log | 7.0 | 203 | 1.1291 | 0.6154 |
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+ | No log | 8.0 | 232 | 1.1157 | 0.6538 |
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+ | No log | 9.0 | 261 | 1.0704 | 0.5769 |
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+ | No log | 10.0 | 290 | 1.2383 | 0.6154 |
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+ | No log | 11.0 | 319 | 1.1518 | 0.5769 |
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+ | No log | 12.0 | 348 | 0.9868 | 0.6923 |
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+ | No log | 13.0 | 377 | 1.0275 | 0.6154 |
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+ | No log | 14.0 | 406 | 1.2089 | 0.6154 |
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+ | No log | 15.0 | 435 | 1.0816 | 0.6923 |
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+ | No log | 16.0 | 464 | 1.2835 | 0.6538 |
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+ | No log | 17.0 | 493 | 1.2866 | 0.6154 |
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+ | 1.2721 | 18.0 | 522 | 1.2825 | 0.5769 |
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+ | 1.2721 | 19.0 | 551 | 1.3226 | 0.5769 |
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+ | 1.2721 | 20.0 | 580 | 1.2800 | 0.5385 |
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+ | 1.2721 | 21.0 | 609 | 1.3184 | 0.6538 |
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+ | 1.2721 | 22.0 | 638 | 1.3373 | 0.6154 |
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+ | 1.2721 | 23.0 | 667 | 1.3510 | 0.6538 |
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+ | 1.2721 | 24.0 | 696 | 1.3206 | 0.5769 |
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+ | 1.2721 | 25.0 | 725 | 1.4753 | 0.5769 |
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+ | 1.2721 | 26.0 | 754 | 1.4773 | 0.5769 |
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+ | 1.2721 | 27.0 | 783 | 1.5285 | 0.5769 |
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+ | 1.2721 | 28.0 | 812 | 1.5013 | 0.6154 |
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+ | 1.2721 | 29.0 | 841 | 1.4610 | 0.5769 |
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+ | 1.2721 | 30.0 | 870 | 1.5523 | 0.5769 |
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+ | 1.2721 | 31.0 | 899 | 1.5938 | 0.6154 |
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+ | 1.2721 | 32.0 | 928 | 1.6204 | 0.5769 |
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+ | 1.2721 | 33.0 | 957 | 1.6790 | 0.5769 |
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+ | 1.2721 | 34.0 | 986 | 1.6347 | 0.5769 |
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+ | 0.4804 | 35.0 | 1015 | 1.5775 | 0.5769 |
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+ | 0.4804 | 36.0 | 1044 | 1.6677 | 0.5769 |
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+ | 0.4804 | 37.0 | 1073 | 1.6337 | 0.5769 |
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+ | 0.4804 | 38.0 | 1102 | 1.6262 | 0.5769 |
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+ | 0.4804 | 39.0 | 1131 | 1.6352 | 0.5769 |
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+ | 0.4804 | 40.0 | 1160 | 1.6363 | 0.5769 |
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  ### Framework versions