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test_roberta-base-uncased_fine

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roberta
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@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7702
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- - Accuracy: 0.5
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  ## Model description
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@@ -50,106 +50,106 @@ 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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- | 10.6938 | 2.0 | 2 | 252.3604 | 0.25 |
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- | 298.9333 | 4.0 | 4 | 442.8570 | 0.25 |
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- | 211.2317 | 6.0 | 6 | 111.0638 | 0.25 |
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- | 106.4107 | 8.0 | 8 | 84.1177 | 0.75 |
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- | 158.3927 | 10.0 | 10 | 51.9647 | 0.75 |
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- | 6.2279 | 12.0 | 12 | 173.9537 | 0.25 |
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- | 182.2623 | 14.0 | 14 | 273.0900 | 0.25 |
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- | 144.4092 | 16.0 | 16 | 118.2153 | 0.25 |
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- | 16.2253 | 18.0 | 18 | 29.9255 | 0.75 |
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- | 61.4584 | 20.0 | 20 | 15.3424 | 0.75 |
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- | 25.5289 | 22.0 | 22 | 73.0185 | 0.25 |
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- | 33.1599 | 24.0 | 24 | 5.7046 | 0.75 |
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- | 16.6906 | 26.0 | 26 | 6.8680 | 0.25 |
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- | 3.3119 | 28.0 | 28 | 25.7839 | 0.25 |
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- | 5.7235 | 30.0 | 30 | 15.8690 | 0.75 |
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- | 34.8772 | 32.0 | 32 | 5.4515 | 0.75 |
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- | 37.1887 | 34.0 | 34 | 77.3684 | 0.25 |
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- | 37.5714 | 36.0 | 36 | 1.4211 | 0.75 |
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- | 14.3135 | 38.0 | 38 | 7.8595 | 0.25 |
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- | 5.5931 | 40.0 | 40 | 16.6094 | 0.25 |
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- | 1.8101 | 42.0 | 42 | 18.0400 | 0.25 |
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- | 4.0269 | 44.0 | 44 | 14.3646 | 0.25 |
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- | 5.9638 | 46.0 | 46 | 11.1460 | 0.25 |
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- | 8.1137 | 48.0 | 48 | 8.4826 | 0.25 |
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- | 8.3957 | 50.0 | 50 | 6.5438 | 0.25 |
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- | 8.5907 | 52.0 | 52 | 5.2709 | 0.25 |
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- | 4.1322 | 54.0 | 54 | 16.3942 | 0.25 |
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- | 4.1029 | 56.0 | 56 | 13.8090 | 0.75 |
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- | 28.9367 | 58.0 | 58 | 5.2299 | 0.75 |
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- | 28.4754 | 60.0 | 60 | 62.0075 | 0.25 |
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- | 30.8988 | 62.0 | 62 | 0.7625 | 0.75 |
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- | 8.1166 | 64.0 | 64 | 12.6710 | 0.25 |
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- | 3.2467 | 66.0 | 66 | 2.3880 | 0.75 |
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- | 10.7889 | 68.0 | 68 | 5.7275 | 0.25 |
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- | 22.3353 | 70.0 | 70 | 12.9041 | 0.75 |
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- | 8.1383 | 72.0 | 72 | 41.1468 | 0.25 |
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- | 36.7992 | 74.0 | 74 | 42.5415 | 0.25 |
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- | 2.0152 | 76.0 | 76 | 20.8100 | 0.75 |
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- | 60.7814 | 78.0 | 78 | 27.4327 | 0.75 |
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- | 34.0779 | 80.0 | 80 | 9.5079 | 0.25 |
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- | 21.0197 | 82.0 | 82 | 24.1783 | 0.25 |
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- | 7.6894 | 84.0 | 84 | 3.8363 | 0.75 |
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- | 7.4756 | 86.0 | 86 | 8.7418 | 0.25 |
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- | 14.3838 | 88.0 | 88 | 7.2120 | 0.75 |
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- | 3.0887 | 90.0 | 90 | 1.2209 | 0.25 |
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- | 1.8247 | 92.0 | 92 | 6.9209 | 0.75 |
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- | 12.0203 | 94.0 | 94 | 12.7842 | 0.25 |
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- | 8.0623 | 96.0 | 96 | 3.4052 | 0.75 |
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- | 2.7705 | 98.0 | 98 | 20.0414 | 0.25 |
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- | 15.1917 | 100.0 | 100 | 1.2432 | 0.75 |
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- | 1.2199 | 102.0 | 102 | 1.3510 | 0.25 |
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- | 10.4742 | 104.0 | 104 | 1.7442 | 0.75 |
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- | 17.1792 | 106.0 | 106 | 29.1314 | 0.25 |
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- | 6.9967 | 108.0 | 108 | 8.8842 | 0.75 |
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- | 27.7392 | 110.0 | 110 | 8.9014 | 0.75 |
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- | 1.9595 | 112.0 | 112 | 10.4839 | 0.25 |
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- | 2.4346 | 114.0 | 114 | 2.5657 | 0.25 |
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- | 9.1093 | 116.0 | 116 | 0.9068 | 0.75 |
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- | 15.7093 | 118.0 | 118 | 25.8976 | 0.25 |
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- | 5.3074 | 120.0 | 120 | 7.7724 | 0.75 |
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- | 21.9532 | 122.0 | 122 | 8.1528 | 0.75 |
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- | 0.9267 | 124.0 | 124 | 26.0336 | 0.25 |
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- | 21.7107 | 126.0 | 126 | 14.6756 | 0.25 |
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- | 9.9152 | 128.0 | 128 | 8.1630 | 0.75 |
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- | 9.7847 | 130.0 | 130 | 7.8175 | 0.25 |
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- | 6.7746 | 132.0 | 132 | 1.0481 | 0.25 |
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- | 14.4615 | 134.0 | 134 | 8.8793 | 0.75 |
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- | 11.8844 | 136.0 | 136 | 9.5880 | 0.25 |
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- | 12.1117 | 138.0 | 138 | 8.3064 | 0.25 |
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- | 8.4027 | 140.0 | 140 | 6.0652 | 0.75 |
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- | 5.8957 | 142.0 | 142 | 13.8286 | 0.25 |
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- | 10.5928 | 144.0 | 144 | 11.3976 | 0.25 |
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- | 5.7989 | 146.0 | 146 | 4.3992 | 0.75 |
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- | 3.2276 | 148.0 | 148 | 14.5699 | 0.25 |
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- | 13.8288 | 150.0 | 150 | 12.2211 | 0.25 |
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- | 2.9975 | 152.0 | 152 | 3.4190 | 0.75 |
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- | 2.5391 | 154.0 | 154 | 13.8731 | 0.25 |
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- | 11.4397 | 156.0 | 156 | 11.4427 | 0.25 |
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- | 4.3493 | 158.0 | 158 | 2.8519 | 0.75 |
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- | 1.8169 | 160.0 | 160 | 4.8652 | 0.25 |
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- | 3.0403 | 162.0 | 162 | 3.1370 | 0.75 |
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- | 5.9224 | 164.0 | 164 | 1.0573 | 0.75 |
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- | 7.1067 | 166.0 | 166 | 14.0748 | 0.25 |
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- | 6.5255 | 168.0 | 168 | 0.7829 | 0.75 |
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- | 5.3116 | 170.0 | 170 | 2.0900 | 0.75 |
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- | 1.927 | 172.0 | 172 | 3.1757 | 0.25 |
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- | 1.8274 | 174.0 | 174 | 0.5881 | 0.75 |
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- | 5.5108 | 176.0 | 176 | 6.2222 | 0.25 |
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- | 1.3478 | 178.0 | 178 | 1.1449 | 0.75 |
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- | 2.7849 | 180.0 | 180 | 3.2430 | 0.25 |
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- | 1.8472 | 182.0 | 182 | 0.5665 | 0.75 |
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- | 1.8895 | 184.0 | 184 | 1.9489 | 0.25 |
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- | 2.4857 | 186.0 | 186 | 0.6363 | 0.75 |
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- | 2.2369 | 188.0 | 188 | 1.2758 | 0.25 |
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- | 1.5309 | 190.0 | 190 | 0.5841 | 0.75 |
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- | 1.7197 | 192.0 | 192 | 0.5974 | 0.75 |
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- | 1.928 | 194.0 | 194 | 0.7480 | 0.25 |
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- | 2.7589 | 196.0 | 196 | 2.8053 | 0.25 |
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- | 1.4242 | 198.0 | 198 | 1.3693 | 0.25 |
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- | 2.1382 | 200.0 | 200 | 0.5714 | 0.75 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6457
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+ - Accuracy: 0.9
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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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+ | 30.4061 | 2.0 | 2 | 273.0057 | 0.25 |
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+ | 34.4778 | 4.0 | 4 | 105.9435 | 0.25 |
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+ | 142.4009 | 6.0 | 6 | 59.4670 | 0.75 |
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+ | 163.2062 | 8.0 | 8 | 7.1859 | 0.75 |
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+ | 18.5088 | 10.0 | 10 | 213.3815 | 0.25 |
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+ | 26.7609 | 12.0 | 12 | 139.8955 | 0.25 |
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+ | 2.5101 | 14.0 | 14 | 40.3215 | 0.75 |
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+ | 227.6862 | 16.0 | 16 | 65.1266 | 0.75 |
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+ | 172.2084 | 18.0 | 18 | 18.4413 | 0.75 |
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+ | 8.9021 | 20.0 | 20 | 135.4651 | 0.25 |
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+ | 18.3707 | 22.0 | 22 | 106.7837 | 0.25 |
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+ | 4.0304 | 24.0 | 24 | 25.2790 | 0.75 |
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+ | 151.1751 | 26.0 | 26 | 40.5055 | 0.75 |
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+ | 90.9441 | 28.0 | 28 | 5.5454 | 0.25 |
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+ | 13.882 | 30.0 | 30 | 163.9310 | 0.25 |
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+ | 21.8757 | 32.0 | 32 | 134.5106 | 0.25 |
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+ | 7.3909 | 34.0 | 34 | 10.2510 | 0.75 |
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+ | 89.2539 | 36.0 | 36 | 24.8699 | 0.75 |
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+ | 41.6868 | 38.0 | 38 | 37.6232 | 0.25 |
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+ | 7.2046 | 40.0 | 40 | 51.7227 | 0.25 |
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+ | 0.785 | 42.0 | 42 | 12.0718 | 0.75 |
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+ | 42.4561 | 44.0 | 44 | 3.2471 | 0.25 |
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+ | 11.7306 | 46.0 | 46 | 96.5822 | 0.25 |
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+ | 11.0079 | 48.0 | 48 | 39.1965 | 0.25 |
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+ | 40.6509 | 50.0 | 50 | 20.8798 | 0.75 |
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+ | 62.2298 | 52.0 | 52 | 3.0547 | 0.75 |
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+ | 9.1953 | 54.0 | 54 | 93.0102 | 0.25 |
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+ | 11.3341 | 56.0 | 56 | 49.3249 | 0.25 |
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+ | 17.2652 | 58.0 | 58 | 12.8465 | 0.75 |
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+ | 26.3375 | 60.0 | 60 | 17.7896 | 0.25 |
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+ | 2.3781 | 62.0 | 62 | 1.1520 | 0.25 |
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+ | 1.7964 | 64.0 | 64 | 27.0024 | 0.25 |
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+ | 0.3859 | 66.0 | 66 | 10.6897 | 0.75 |
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+ | 43.8049 | 68.0 | 68 | 4.2678 | 0.75 |
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+ | 5.7809 | 70.0 | 70 | 57.0428 | 0.25 |
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+ | 5.8372 | 72.0 | 72 | 3.1891 | 0.25 |
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+ | 10.2265 | 74.0 | 74 | 14.5562 | 0.25 |
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+ | 1.3022 | 76.0 | 76 | 0.9098 | 0.75 |
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+ | 3.1084 | 78.0 | 78 | 11.1294 | 0.25 |
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+ | 26.8542 | 80.0 | 80 | 8.2287 | 0.75 |
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+ | 1.3357 | 82.0 | 82 | 50.3411 | 0.25 |
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+ | 9.7622 | 84.0 | 84 | 56.3544 | 0.25 |
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+ | 2.3044 | 86.0 | 86 | 11.6592 | 0.75 |
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+ | 65.6323 | 88.0 | 88 | 17.1945 | 0.75 |
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+ | 26.2342 | 90.0 | 90 | 32.7401 | 0.25 |
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+ | 6.1743 | 92.0 | 92 | 50.0640 | 0.25 |
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+ | 3.0945 | 94.0 | 94 | 8.6429 | 0.75 |
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+ | 55.6696 | 96.0 | 96 | 11.5617 | 0.75 |
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+ | 7.9304 | 98.0 | 98 | 48.5339 | 0.25 |
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+ | 9.4683 | 100.0 | 100 | 68.6256 | 0.25 |
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+ | 6.9711 | 102.0 | 102 | 1.1185 | 0.25 |
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+ | 17.9561 | 104.0 | 104 | 2.0326 | 0.75 |
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+ | 3.8259 | 106.0 | 106 | 28.7270 | 0.25 |
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+ | 1.4343 | 108.0 | 108 | 7.2848 | 0.75 |
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+ | 39.3397 | 110.0 | 110 | 5.9552 | 0.75 |
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+ | 2.2064 | 112.0 | 112 | 23.7964 | 0.25 |
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+ | 1.8151 | 114.0 | 114 | 5.3844 | 0.75 |
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+ | 22.2713 | 116.0 | 116 | 2.2849 | 0.75 |
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+ | 3.3845 | 118.0 | 118 | 35.3856 | 0.25 |
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+ | 3.4312 | 120.0 | 120 | 0.6936 | 0.25 |
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+ | 6.1348 | 122.0 | 122 | 9.6259 | 0.25 |
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+ | 0.4537 | 124.0 | 124 | 5.0600 | 0.75 |
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+ | 19.9785 | 126.0 | 126 | 1.4862 | 0.25 |
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+ | 3.5936 | 128.0 | 128 | 44.3517 | 0.25 |
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+ | 5.9722 | 130.0 | 130 | 18.2233 | 0.25 |
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+ | 20.099 | 132.0 | 132 | 9.5809 | 0.75 |
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+ | 28.7009 | 134.0 | 134 | 2.0241 | 0.75 |
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+ | 3.8411 | 136.0 | 136 | 39.1799 | 0.25 |
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+ | 5.2586 | 138.0 | 138 | 21.3355 | 0.25 |
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+ | 8.9217 | 140.0 | 140 | 5.3869 | 0.75 |
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+ | 14.4647 | 142.0 | 142 | 6.8343 | 0.25 |
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+ | 0.6143 | 144.0 | 144 | 2.6079 | 0.25 |
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+ | 0.3063 | 146.0 | 146 | 0.6002 | 0.75 |
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+ | 0.0396 | 148.0 | 148 | 20.4224 | 0.25 |
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+ | 3.2237 | 150.0 | 150 | 14.8742 | 0.25 |
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+ | 6.1285 | 152.0 | 152 | 2.8047 | 0.75 |
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+ | 6.9479 | 154.0 | 154 | 15.0406 | 0.25 |
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+ | 2.3471 | 156.0 | 156 | 13.5490 | 0.25 |
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+ | 3.6263 | 158.0 | 158 | 1.4868 | 0.75 |
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+ | 0.5022 | 160.0 | 160 | 17.8967 | 0.25 |
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+ | 4.1843 | 162.0 | 162 | 18.0276 | 0.25 |
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+ | 0.7145 | 164.0 | 164 | 4.3462 | 0.75 |
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+ | 23.1296 | 166.0 | 166 | 6.6729 | 0.75 |
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+ | 13.1642 | 168.0 | 168 | 3.9175 | 0.25 |
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+ | 3.433 | 170.0 | 170 | 33.4045 | 0.25 |
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+ | 5.0543 | 172.0 | 172 | 31.1038 | 0.25 |
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+ | 2.695 | 174.0 | 174 | 6.2978 | 0.25 |
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+ | 11.396 | 176.0 | 176 | 5.3975 | 0.75 |
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+ | 20.3118 | 178.0 | 178 | 4.1132 | 0.75 |
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+ | 4.1789 | 180.0 | 180 | 9.2370 | 0.25 |
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+ | 2.806 | 182.0 | 182 | 16.7589 | 0.25 |
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+ | 1.8424 | 184.0 | 184 | 7.5781 | 0.25 |
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+ | 3.0288 | 186.0 | 186 | 1.7304 | 0.75 |
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+ | 5.4305 | 188.0 | 188 | 0.8391 | 0.75 |
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+ | 1.9329 | 190.0 | 190 | 9.1368 | 0.25 |
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+ | 1.8576 | 192.0 | 192 | 12.6123 | 0.25 |
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+ | 2.0932 | 194.0 | 194 | 8.6446 | 0.25 |
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+ | 0.5404 | 196.0 | 196 | 1.8219 | 0.25 |
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+ | 2.7355 | 198.0 | 198 | 0.5940 | 0.75 |
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+ | 2.1872 | 200.0 | 200 | 0.7259 | 0.25 |
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  ### Framework versions