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update model card README.md

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@@ -19,11 +19,11 @@ 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: 0.2909
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- - Accuracy: 0.9362
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- - F1: 0.9354
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- - Precision: 0.9380
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- - Recall: 0.9362
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  ## Model description
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@@ -55,36 +55,36 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 2.4251 | 1.0 | 71 | 1.8259 | 0.8688 | 0.8615 | 0.8645 | 0.8688 |
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- | 1.34 | 2.0 | 142 | 0.8796 | 0.9078 | 0.8978 | 0.8929 | 0.9078 |
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- | 0.6342 | 3.0 | 213 | 0.5158 | 0.9113 | 0.9052 | 0.9078 | 0.9113 |
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- | 0.3265 | 4.0 | 284 | 0.3381 | 0.9326 | 0.9268 | 0.9254 | 0.9326 |
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- | 0.165 | 5.0 | 355 | 0.3140 | 0.9255 | 0.9201 | 0.9215 | 0.9255 |
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- | 0.0939 | 6.0 | 426 | 0.2805 | 0.9291 | 0.9252 | 0.9279 | 0.9291 |
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- | 0.0568 | 7.0 | 497 | 0.2679 | 0.9362 | 0.9308 | 0.9290 | 0.9362 |
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- | 0.0337 | 8.0 | 568 | 0.2728 | 0.9291 | 0.9227 | 0.9217 | 0.9291 |
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- | 0.0216 | 9.0 | 639 | 0.2531 | 0.9362 | 0.9355 | 0.9379 | 0.9362 |
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- | 0.0141 | 10.0 | 710 | 0.2741 | 0.9326 | 0.9325 | 0.9362 | 0.9326 |
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- | 0.0108 | 11.0 | 781 | 0.2749 | 0.9291 | 0.9278 | 0.9302 | 0.9291 |
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- | 0.0086 | 12.0 | 852 | 0.2680 | 0.9291 | 0.9278 | 0.9302 | 0.9291 |
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- | 0.0074 | 13.0 | 923 | 0.2688 | 0.9326 | 0.9303 | 0.9317 | 0.9326 |
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- | 0.0065 | 14.0 | 994 | 0.2736 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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- | 0.0057 | 15.0 | 1065 | 0.2780 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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- | 0.0051 | 16.0 | 1136 | 0.2730 | 0.9362 | 0.9323 | 0.9321 | 0.9362 |
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- | 0.0047 | 17.0 | 1207 | 0.2793 | 0.9362 | 0.9344 | 0.9361 | 0.9362 |
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- | 0.0044 | 18.0 | 1278 | 0.2784 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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- | 0.0039 | 19.0 | 1349 | 0.2799 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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- | 0.0036 | 20.0 | 1420 | 0.2820 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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- | 0.0035 | 21.0 | 1491 | 0.2836 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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- | 0.0032 | 22.0 | 1562 | 0.2851 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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- | 0.0032 | 23.0 | 1633 | 0.2863 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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- | 0.0031 | 24.0 | 1704 | 0.2901 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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- | 0.0029 | 25.0 | 1775 | 0.2896 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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- | 0.0028 | 26.0 | 1846 | 0.2892 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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- | 0.0027 | 27.0 | 1917 | 0.2891 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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- | 0.0026 | 28.0 | 1988 | 0.2898 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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- | 0.0027 | 29.0 | 2059 | 0.2909 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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- | 0.0026 | 30.0 | 2130 | 0.2909 | 0.9362 | 0.9354 | 0.9380 | 0.9362 |
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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: 0.2292
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+ - Accuracy: 0.9504
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+ - F1: 0.9489
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+ - Precision: 0.9510
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+ - Recall: 0.9504
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 2.404 | 1.0 | 71 | 1.7840 | 0.8865 | 0.8776 | 0.8785 | 0.8865 |
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+ | 1.295 | 2.0 | 142 | 0.8539 | 0.8972 | 0.8871 | 0.8803 | 0.8972 |
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+ | 0.6186 | 3.0 | 213 | 0.4818 | 0.9326 | 0.9263 | 0.9266 | 0.9326 |
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+ | 0.3103 | 4.0 | 284 | 0.3101 | 0.9397 | 0.9343 | 0.9324 | 0.9397 |
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+ | 0.1618 | 5.0 | 355 | 0.3001 | 0.9291 | 0.9251 | 0.9278 | 0.9291 |
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+ | 0.0893 | 6.0 | 426 | 0.2743 | 0.9291 | 0.9251 | 0.9276 | 0.9291 |
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+ | 0.0547 | 7.0 | 497 | 0.2605 | 0.9255 | 0.9236 | 0.9334 | 0.9255 |
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+ | 0.028 | 8.0 | 568 | 0.2167 | 0.9397 | 0.9375 | 0.9403 | 0.9397 |
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+ | 0.0186 | 9.0 | 639 | 0.2096 | 0.9468 | 0.9467 | 0.9499 | 0.9468 |
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+ | 0.0134 | 10.0 | 710 | 0.2219 | 0.9362 | 0.9354 | 0.9402 | 0.9362 |
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+ | 0.0107 | 11.0 | 781 | 0.2124 | 0.9468 | 0.9466 | 0.9507 | 0.9468 |
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+ | 0.0087 | 12.0 | 852 | 0.2119 | 0.9504 | 0.9497 | 0.9534 | 0.9504 |
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+ | 0.0075 | 13.0 | 923 | 0.2141 | 0.9504 | 0.9497 | 0.9534 | 0.9504 |
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+ | 0.0066 | 14.0 | 994 | 0.2198 | 0.9433 | 0.9415 | 0.9442 | 0.9433 |
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+ | 0.0058 | 15.0 | 1065 | 0.2188 | 0.9468 | 0.9454 | 0.9474 | 0.9468 |
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+ | 0.0052 | 16.0 | 1136 | 0.2181 | 0.9468 | 0.9454 | 0.9474 | 0.9468 |
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+ | 0.0047 | 17.0 | 1207 | 0.2220 | 0.9504 | 0.9489 | 0.9510 | 0.9504 |
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+ | 0.0044 | 18.0 | 1278 | 0.2232 | 0.9504 | 0.9489 | 0.9510 | 0.9504 |
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+ | 0.004 | 19.0 | 1349 | 0.2216 | 0.9539 | 0.9535 | 0.9565 | 0.9539 |
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+ | 0.0037 | 20.0 | 1420 | 0.2251 | 0.9504 | 0.9489 | 0.9510 | 0.9504 |
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+ | 0.0036 | 21.0 | 1491 | 0.2275 | 0.9468 | 0.9451 | 0.9470 | 0.9468 |
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+ | 0.0034 | 22.0 | 1562 | 0.2264 | 0.9539 | 0.9535 | 0.9565 | 0.9539 |
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+ | 0.0032 | 23.0 | 1633 | 0.2283 | 0.9504 | 0.9489 | 0.9510 | 0.9504 |
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+ | 0.003 | 24.0 | 1704 | 0.2299 | 0.9504 | 0.9489 | 0.9510 | 0.9504 |
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+ | 0.0029 | 25.0 | 1775 | 0.2282 | 0.9468 | 0.9451 | 0.9470 | 0.9468 |
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+ | 0.0029 | 26.0 | 1846 | 0.2288 | 0.9468 | 0.9451 | 0.9470 | 0.9468 |
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+ | 0.0028 | 27.0 | 1917 | 0.2286 | 0.9504 | 0.9489 | 0.9510 | 0.9504 |
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+ | 0.0027 | 28.0 | 1988 | 0.2293 | 0.9504 | 0.9489 | 0.9510 | 0.9504 |
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+ | 0.0026 | 29.0 | 2059 | 0.2291 | 0.9504 | 0.9489 | 0.9510 | 0.9504 |
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+ | 0.0026 | 30.0 | 2130 | 0.2292 | 0.9504 | 0.9489 | 0.9510 | 0.9504 |
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  ### Framework versions