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@@ -14,7 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0003
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  ## Model description
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@@ -45,86 +45,86 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.0439 | 1.0 | 30 | 0.0535 |
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- | 0.0415 | 2.0 | 60 | 0.0434 |
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- | 0.0289 | 3.0 | 90 | 0.0293 |
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- | 0.0046 | 4.0 | 120 | 0.0171 |
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- | 0.0021 | 5.0 | 150 | 0.0066 |
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- | 0.0006 | 6.0 | 180 | 0.0051 |
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- | 0.0003 | 7.0 | 210 | 0.0032 |
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- | 0.0006 | 8.0 | 240 | 0.0024 |
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- | 0.0031 | 9.0 | 270 | 0.0040 |
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- | 0.0002 | 10.0 | 300 | 0.0031 |
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- | 0.0001 | 11.0 | 330 | 0.0016 |
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- | 0.0038 | 12.0 | 360 | 0.0015 |
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- | 0.0001 | 13.0 | 390 | 0.0018 |
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- | 0.0001 | 14.0 | 420 | 0.0020 |
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- | 0.0001 | 15.0 | 450 | 0.0023 |
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- | 0.0001 | 16.0 | 480 | 0.0019 |
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- | 0.0001 | 17.0 | 510 | 0.0027 |
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- | 0.0001 | 18.0 | 540 | 0.0024 |
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- | 0.0001 | 19.0 | 570 | 0.0010 |
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- | 0.0001 | 20.0 | 600 | 0.0011 |
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- | 0.0001 | 21.0 | 630 | 0.0012 |
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- | 0.0001 | 22.0 | 660 | 0.0012 |
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- | 0.0001 | 23.0 | 690 | 0.0012 |
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- | 0.0001 | 24.0 | 720 | 0.0011 |
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- | 0.0 | 25.0 | 750 | 0.0013 |
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- | 0.0002 | 26.0 | 780 | 0.0006 |
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- | 0.0001 | 27.0 | 810 | 0.0012 |
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- | 0.0001 | 28.0 | 840 | 0.0007 |
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- | 0.0001 | 29.0 | 870 | 0.0008 |
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- | 0.0 | 30.0 | 900 | 0.0009 |
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- | 0.0001 | 31.0 | 930 | 0.0009 |
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- | 0.0001 | 32.0 | 960 | 0.0006 |
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- | 0.0 | 33.0 | 990 | 0.0005 |
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- | 0.0 | 34.0 | 1020 | 0.0005 |
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- | 0.0 | 35.0 | 1050 | 0.0005 |
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- | 0.0001 | 36.0 | 1080 | 0.0008 |
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- | 0.0001 | 37.0 | 1110 | 0.0006 |
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- | 0.0001 | 38.0 | 1140 | 0.0005 |
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- | 0.0 | 39.0 | 1170 | 0.0007 |
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- | 0.0001 | 40.0 | 1200 | 0.0010 |
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- | 0.0002 | 41.0 | 1230 | 0.0009 |
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- | 0.0 | 42.0 | 1260 | 0.0007 |
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- | 0.0 | 43.0 | 1290 | 0.0005 |
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- | 0.0001 | 44.0 | 1320 | 0.0005 |
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- | 0.0 | 45.0 | 1350 | 0.0005 |
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- | 0.0 | 46.0 | 1380 | 0.0005 |
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- | 0.0 | 47.0 | 1410 | 0.0005 |
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- | 0.0 | 48.0 | 1440 | 0.0005 |
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- | 0.0001 | 49.0 | 1470 | 0.0005 |
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- | 0.0 | 50.0 | 1500 | 0.0006 |
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- | 0.0 | 51.0 | 1530 | 0.0006 |
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- | 0.0 | 52.0 | 1560 | 0.0005 |
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- | 0.0 | 53.0 | 1590 | 0.0006 |
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- | 0.0 | 54.0 | 1620 | 0.0006 |
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- | 0.0 | 55.0 | 1650 | 0.0006 |
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- | 0.0 | 56.0 | 1680 | 0.0007 |
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- | 0.0 | 57.0 | 1710 | 0.0007 |
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- | 0.0 | 58.0 | 1740 | 0.0007 |
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- | 0.0 | 59.0 | 1770 | 0.0007 |
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- | 0.0 | 60.0 | 1800 | 0.0006 |
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- | 0.0 | 61.0 | 1830 | 0.0007 |
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- | 0.0 | 62.0 | 1860 | 0.0006 |
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- | 0.0 | 63.0 | 1890 | 0.0006 |
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- | 0.0 | 64.0 | 1920 | 0.0003 |
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- | 0.0 | 65.0 | 1950 | 0.0003 |
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- | 0.0 | 66.0 | 1980 | 0.0003 |
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- | 0.0 | 67.0 | 2010 | 0.0003 |
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- | 0.0 | 68.0 | 2040 | 0.0003 |
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- | 0.0 | 69.0 | 2070 | 0.0003 |
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- | 0.0 | 70.0 | 2100 | 0.0003 |
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- | 0.0 | 71.0 | 2130 | 0.0003 |
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- | 0.0 | 72.0 | 2160 | 0.0003 |
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- | 0.0 | 73.0 | 2190 | 0.0003 |
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- | 0.0 | 74.0 | 2220 | 0.0003 |
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- | 0.0 | 75.0 | 2250 | 0.0003 |
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- | 0.0 | 76.0 | 2280 | 0.0003 |
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- | 0.0 | 77.0 | 2310 | 0.0003 |
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- | 0.0 | 78.0 | 2340 | 0.0003 |
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- | 0.0 | 79.0 | 2370 | 0.0003 |
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- | 0.0 | 80.0 | 2400 | 0.0003 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0244
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.0983 | 1.0 | 11 | 0.0699 |
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+ | 0.0481 | 2.0 | 22 | 0.0476 |
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+ | 0.0367 | 3.0 | 33 | 0.0445 |
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+ | 0.0264 | 4.0 | 44 | 0.0423 |
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+ | 0.0336 | 5.0 | 55 | 0.0390 |
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+ | 0.025 | 6.0 | 66 | 0.0410 |
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+ | 0.0141 | 7.0 | 77 | 0.0425 |
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+ | 0.0121 | 8.0 | 88 | 0.0371 |
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+ | 0.0075 | 9.0 | 99 | 0.0293 |
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+ | 0.011 | 10.0 | 110 | 0.0344 |
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+ | 0.012 | 11.0 | 121 | 0.0304 |
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+ | 0.0029 | 12.0 | 132 | 0.0313 |
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+ | 0.0026 | 13.0 | 143 | 0.0303 |
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+ | 0.0004 | 14.0 | 154 | 0.0298 |
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+ | 0.0008 | 15.0 | 165 | 0.0288 |
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+ | 0.0002 | 16.0 | 176 | 0.0286 |
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+ | 0.0003 | 17.0 | 187 | 0.0319 |
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+ | 0.0004 | 18.0 | 198 | 0.0332 |
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+ | 0.0003 | 19.0 | 209 | 0.0423 |
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+ | 0.0011 | 20.0 | 220 | 0.0244 |
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+ | 0.0002 | 21.0 | 231 | 0.0255 |
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+ | 0.0003 | 22.0 | 242 | 0.0264 |
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+ | 0.0003 | 23.0 | 253 | 0.0239 |
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+ | 0.0001 | 24.0 | 264 | 0.0216 |
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+ | 0.0001 | 25.0 | 275 | 0.0212 |
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+ | 0.0002 | 26.0 | 286 | 0.0222 |
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+ | 0.0001 | 27.0 | 297 | 0.0226 |
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+ | 0.0004 | 28.0 | 308 | 0.0214 |
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+ | 0.0001 | 29.0 | 319 | 0.0223 |
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+ | 0.0001 | 30.0 | 330 | 0.0228 |
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+ | 0.0001 | 31.0 | 341 | 0.0225 |
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+ | 0.0002 | 32.0 | 352 | 0.0222 |
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+ | 0.0001 | 33.0 | 363 | 0.0233 |
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+ | 0.0003 | 34.0 | 374 | 0.0340 |
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+ | 0.0002 | 35.0 | 385 | 0.0321 |
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+ | 0.0001 | 36.0 | 396 | 0.0203 |
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+ | 0.0004 | 37.0 | 407 | 0.0205 |
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+ | 0.0002 | 38.0 | 418 | 0.0270 |
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+ | 0.0001 | 39.0 | 429 | 0.0204 |
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+ | 0.0001 | 40.0 | 440 | 0.0187 |
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+ | 0.0002 | 41.0 | 451 | 0.0223 |
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+ | 0.0002 | 42.0 | 462 | 0.0279 |
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+ | 0.0001 | 43.0 | 473 | 0.0302 |
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+ | 0.0001 | 44.0 | 484 | 0.0286 |
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+ | 0.0001 | 45.0 | 495 | 0.0202 |
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+ | 0.0001 | 46.0 | 506 | 0.0219 |
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+ | 0.0001 | 47.0 | 517 | 0.0227 |
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+ | 0.0001 | 48.0 | 528 | 0.0234 |
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+ | 0.0001 | 49.0 | 539 | 0.0235 |
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+ | 0.0001 | 50.0 | 550 | 0.0234 |
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+ | 0.0001 | 51.0 | 561 | 0.0234 |
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+ | 0.0001 | 52.0 | 572 | 0.0233 |
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+ | 0.0001 | 53.0 | 583 | 0.0237 |
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+ | 0.0001 | 54.0 | 594 | 0.0238 |
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+ | 0.0001 | 55.0 | 605 | 0.0237 |
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+ | 0.0001 | 56.0 | 616 | 0.0236 |
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+ | 0.0001 | 57.0 | 627 | 0.0238 |
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+ | 0.0 | 58.0 | 638 | 0.0236 |
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+ | 0.0 | 59.0 | 649 | 0.0235 |
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+ | 0.0001 | 60.0 | 660 | 0.0236 |
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+ | 0.0001 | 61.0 | 671 | 0.0236 |
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+ | 0.0 | 62.0 | 682 | 0.0235 |
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+ | 0.0001 | 63.0 | 693 | 0.0302 |
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+ | 0.0001 | 64.0 | 704 | 0.0304 |
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+ | 0.0001 | 65.0 | 715 | 0.0239 |
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+ | 0.0 | 66.0 | 726 | 0.0231 |
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+ | 0.0001 | 67.0 | 737 | 0.0229 |
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+ | 0.0001 | 68.0 | 748 | 0.0228 |
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+ | 0.0 | 69.0 | 759 | 0.0226 |
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+ | 0.0004 | 70.0 | 770 | 0.0226 |
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+ | 0.0001 | 71.0 | 781 | 0.0232 |
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+ | 0.0001 | 72.0 | 792 | 0.0235 |
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+ | 0.0001 | 73.0 | 803 | 0.0236 |
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+ | 0.0002 | 74.0 | 814 | 0.0237 |
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+ | 0.0001 | 75.0 | 825 | 0.0238 |
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+ | 0.0001 | 76.0 | 836 | 0.0241 |
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+ | 0.0 | 77.0 | 847 | 0.0244 |
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+ | 0.0001 | 78.0 | 858 | 0.0244 |
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+ | 0.0001 | 79.0 | 869 | 0.0244 |
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+ | 0.0001 | 80.0 | 880 | 0.0244 |
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  ### Framework versions