metadata
base_model: cardiffnlp/twitter-roberta-base-2019-90m
tags:
- generated_from_trainer
model-index:
- name: 2020-Q4-75p-filtered
results: []
2020-Q4-75p-filtered
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-2019-90m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.0907
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 4.1e-07
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2400000
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.07 | 8000 | 3.5132 |
| 3.7013 | 0.13 | 16000 | 3.4076 |
| 3.7013 | 0.2 | 24000 | 3.3552 |
| 3.4836 | 0.27 | 32000 | 3.3266 |
| 3.4836 | 0.34 | 40000 | 3.3065 |
| 3.4297 | 0.4 | 48000 | 3.2915 |
| 3.4297 | 0.47 | 56000 | 3.2709 |
| 3.4017 | 0.54 | 64000 | 3.2550 |
| 3.4017 | 0.61 | 72000 | 3.2550 |
| 3.3841 | 0.67 | 80000 | 3.2372 |
| 3.3841 | 0.74 | 88000 | 3.2474 |
| 3.3749 | 0.81 | 96000 | 3.2446 |
| 3.3749 | 0.88 | 104000 | 3.2282 |
| 3.36 | 0.94 | 112000 | 3.2236 |
| 3.36 | 1.01 | 120000 | 3.2212 |
| 3.3556 | 1.08 | 128000 | 3.2011 |
| 3.3556 | 1.15 | 136000 | 3.2182 |
| 3.3516 | 1.21 | 144000 | 3.2046 |
| 3.3516 | 1.28 | 152000 | 3.2080 |
| 3.3485 | 1.35 | 160000 | 3.2197 |
| 3.3485 | 1.41 | 168000 | 3.1972 |
| 3.3429 | 1.48 | 176000 | 3.1990 |
| 3.3429 | 1.55 | 184000 | 3.1921 |
| 3.3383 | 1.62 | 192000 | 3.1891 |
| 3.3383 | 1.68 | 200000 | 3.1740 |
| 3.3352 | 1.75 | 208000 | 3.2062 |
| 3.3352 | 1.82 | 216000 | 3.1934 |
| 3.3376 | 1.89 | 224000 | 3.1893 |
| 3.3376 | 1.95 | 232000 | 3.1887 |
| 3.3272 | 2.02 | 240000 | 3.1821 |
| 3.3272 | 2.09 | 248000 | 3.1921 |
| 3.3329 | 2.16 | 256000 | 3.1812 |
| 3.3329 | 2.22 | 264000 | 3.1753 |
| 3.3241 | 2.29 | 272000 | 3.1790 |
| 3.3241 | 2.36 | 280000 | 3.1863 |
| 3.3271 | 2.43 | 288000 | 3.1850 |
| 3.3271 | 2.49 | 296000 | 3.1801 |
| 3.3223 | 2.56 | 304000 | 3.1687 |
| 3.3223 | 2.63 | 312000 | 3.1893 |
| 3.3211 | 2.69 | 320000 | 3.1691 |
| 3.3211 | 2.76 | 328000 | 3.1733 |
| 3.3226 | 2.83 | 336000 | 3.1659 |
| 3.3226 | 2.9 | 344000 | 3.1714 |
| 3.322 | 2.96 | 352000 | 3.1815 |
| 3.322 | 3.03 | 360000 | 3.1711 |
| 3.3094 | 3.1 | 368000 | 3.1669 |
| 3.3094 | 3.17 | 376000 | 3.1664 |
| 3.3172 | 3.23 | 384000 | 3.1541 |
| 3.3172 | 3.3 | 392000 | 3.1747 |
| 3.3134 | 3.37 | 400000 | 3.1648 |
| 3.3134 | 3.44 | 408000 | 3.1585 |
| 3.3194 | 3.5 | 416000 | 3.1651 |
| 3.3194 | 3.57 | 424000 | 3.1618 |
| 3.3199 | 3.64 | 432000 | 3.1566 |
| 3.3199 | 3.71 | 440000 | 3.1475 |
| 3.3185 | 3.77 | 448000 | 3.1504 |
| 3.3185 | 3.84 | 456000 | 3.1551 |
| 3.3072 | 3.91 | 464000 | 3.1636 |
| 3.3072 | 3.97 | 472000 | 3.1428 |
| 3.3103 | 4.04 | 480000 | 3.1537 |
| 3.3103 | 4.11 | 488000 | 3.1576 |
| 3.3106 | 4.18 | 496000 | 3.1442 |
| 3.3106 | 4.24 | 504000 | 3.1485 |
| 3.3091 | 4.31 | 512000 | 3.1377 |
| 3.3091 | 4.38 | 520000 | 3.1325 |
| 3.3051 | 4.45 | 528000 | 3.1570 |
| 3.3051 | 4.51 | 536000 | 3.1509 |
| 3.3034 | 4.58 | 544000 | 3.1481 |
| 3.3034 | 4.65 | 552000 | 3.1442 |
| 3.3076 | 4.72 | 560000 | 3.1451 |
| 3.3076 | 4.78 | 568000 | 3.1394 |
| 3.307 | 4.85 | 576000 | 3.1405 |
| 3.307 | 4.92 | 584000 | 3.1407 |
| 3.2994 | 4.99 | 592000 | 3.1483 |
| 3.2994 | 5.05 | 600000 | 3.1332 |
| 3.3017 | 5.12 | 608000 | 3.1447 |
| 3.3017 | 5.19 | 616000 | 3.1423 |
| 3.2931 | 5.25 | 624000 | 3.1427 |
| 3.2931 | 5.32 | 632000 | 3.1359 |
| 3.3042 | 5.39 | 640000 | 3.1399 |
| 3.3042 | 5.46 | 648000 | 3.1370 |
| 3.3006 | 5.52 | 656000 | 3.1319 |
| 3.3006 | 5.59 | 664000 | 3.1309 |
| 3.2973 | 5.66 | 672000 | 3.1408 |
| 3.2973 | 5.73 | 680000 | 3.1272 |
| 3.3023 | 5.79 | 688000 | 3.1403 |
| 3.3023 | 5.86 | 696000 | 3.1422 |
| 3.2968 | 5.93 | 704000 | 3.1204 |
| 3.2968 | 6.0 | 712000 | 3.1341 |
| 3.2982 | 6.06 | 720000 | 3.1381 |
| 3.2982 | 6.13 | 728000 | 3.1435 |
| 3.296 | 6.2 | 736000 | 3.1425 |
| 3.296 | 6.27 | 744000 | 3.1182 |
| 3.2949 | 6.33 | 752000 | 3.1336 |
| 3.2949 | 6.4 | 760000 | 3.1314 |
| 3.2925 | 6.47 | 768000 | 3.1347 |
| 3.2925 | 6.53 | 776000 | 3.1296 |
| 3.2981 | 6.6 | 784000 | 3.1308 |
| 3.2981 | 6.67 | 792000 | 3.1367 |
| 3.2904 | 6.74 | 800000 | 3.1176 |
| 3.2904 | 6.8 | 808000 | 3.1444 |
| 3.2936 | 6.87 | 816000 | 3.1213 |
| 3.2936 | 6.94 | 824000 | 3.1236 |
| 3.2856 | 7.01 | 832000 | 3.1276 |
| 3.2856 | 7.07 | 840000 | 3.1220 |
| 3.2956 | 7.14 | 848000 | 3.1211 |
| 3.2956 | 7.21 | 856000 | 3.1225 |
| 3.2872 | 7.28 | 864000 | 3.1220 |
| 3.2872 | 7.34 | 872000 | 3.1148 |
| 3.291 | 7.41 | 880000 | 3.1317 |
| 3.291 | 7.48 | 888000 | 3.1204 |
| 3.2923 | 7.55 | 896000 | 3.1148 |
| 3.2923 | 7.61 | 904000 | 3.1196 |
| 3.294 | 7.68 | 912000 | 3.1232 |
| 3.294 | 7.75 | 920000 | 3.1184 |
| 3.2838 | 7.81 | 928000 | 3.1157 |
| 3.2838 | 7.88 | 936000 | 3.1112 |
| 3.2848 | 7.95 | 944000 | 3.1097 |
| 3.2848 | 8.02 | 952000 | 3.1136 |
| 3.2797 | 8.08 | 960000 | 3.1108 |
| 3.2797 | 8.15 | 968000 | 3.1149 |
| 3.2852 | 8.22 | 976000 | 3.1050 |
| 3.2852 | 8.29 | 984000 | 3.0962 |
| 3.2833 | 8.35 | 992000 | 3.1139 |
| 3.2833 | 8.42 | 1000000 | 3.1099 |
| 3.2819 | 8.49 | 1008000 | 3.1126 |
| 3.2819 | 8.56 | 1016000 | 3.1167 |
| 3.2825 | 8.62 | 1024000 | 3.1057 |
| 3.2825 | 8.69 | 1032000 | 3.1059 |
| 3.2744 | 8.76 | 1040000 | 3.1075 |
| 3.2744 | 8.83 | 1048000 | 3.1068 |
| 3.2864 | 8.89 | 1056000 | 3.1098 |
| 3.2864 | 8.96 | 1064000 | 3.1151 |
| 3.2783 | 9.03 | 1072000 | 3.1022 |
| 3.2783 | 9.09 | 1080000 | 3.1196 |
| 3.2865 | 9.16 | 1088000 | 3.1177 |
| 3.2865 | 9.23 | 1096000 | 3.0985 |
| 3.2799 | 9.3 | 1104000 | 3.1073 |
| 3.2799 | 9.36 | 1112000 | 3.1019 |
| 3.2754 | 9.43 | 1120000 | 3.1003 |
| 3.2754 | 9.5 | 1128000 | 3.1015 |
| 3.2654 | 9.57 | 1136000 | 3.1047 |
| 3.2654 | 9.63 | 1144000 | 3.0931 |
| 3.2775 | 9.7 | 1152000 | 3.1130 |
| 3.2775 | 9.77 | 1160000 | 3.1094 |
| 3.2811 | 9.84 | 1168000 | 3.0964 |
| 3.2811 | 9.9 | 1176000 | 3.1069 |
| 3.2745 | 9.97 | 1184000 | 3.0995 |
| 3.2745 | 10.04 | 1192000 | 3.1167 |
| 3.2811 | 10.11 | 1200000 | 3.1119 |
| 3.2811 | 10.17 | 1208000 | 3.1063 |
| 3.2761 | 10.24 | 1216000 | 3.1041 |
| 3.2761 | 10.31 | 1224000 | 3.1044 |
| 3.2786 | 10.37 | 1232000 | 3.1051 |
| 3.2786 | 10.44 | 1240000 | 3.1068 |
| 3.2746 | 10.51 | 1248000 | 3.1057 |
| 3.2746 | 10.58 | 1256000 | 3.1009 |
| 3.2777 | 10.64 | 1264000 | 3.1103 |
| 3.2777 | 10.71 | 1272000 | 3.1073 |
| 3.268 | 10.78 | 1280000 | 3.1044 |
| 3.268 | 10.85 | 1288000 | 3.0951 |
| 3.266 | 10.91 | 1296000 | 3.1160 |
| 3.266 | 10.98 | 1304000 | 3.1156 |
| 3.2689 | 11.05 | 1312000 | 3.1033 |
| 3.2689 | 11.12 | 1320000 | 3.0985 |
| 3.2732 | 11.18 | 1328000 | 3.1103 |
| 3.2732 | 11.25 | 1336000 | 3.1059 |
| 3.2732 | 11.32 | 1344000 | 3.0810 |
| 3.2732 | 11.39 | 1352000 | 3.1074 |
| 3.2735 | 11.45 | 1360000 | 3.1070 |
| 3.2735 | 11.52 | 1368000 | 3.0996 |
| 3.2794 | 11.59 | 1376000 | 3.0987 |
| 3.2794 | 11.65 | 1384000 | 3.0890 |
| 3.2695 | 11.72 | 1392000 | 3.0998 |
| 3.2695 | 11.79 | 1400000 | 3.1010 |
| 3.2725 | 11.86 | 1408000 | 3.0921 |
| 3.2725 | 11.92 | 1416000 | 3.0921 |
| 3.2757 | 11.99 | 1424000 | 3.0949 |
| 3.2757 | 12.06 | 1432000 | 3.0957 |
| 3.2757 | 12.13 | 1440000 | 3.0918 |
| 3.2757 | 12.19 | 1448000 | 3.1131 |
| 3.2582 | 12.26 | 1456000 | 3.1006 |
| 3.2582 | 12.33 | 1464000 | 3.0912 |
| 3.2741 | 12.4 | 1472000 | 3.0938 |
| 3.2741 | 12.46 | 1480000 | 3.0977 |
| 3.2725 | 12.53 | 1488000 | 3.0973 |
| 3.2725 | 12.6 | 1496000 | 3.1070 |
| 3.2658 | 12.67 | 1504000 | 3.0992 |
| 3.2658 | 12.73 | 1512000 | 3.0927 |
| 3.2706 | 12.8 | 1520000 | 3.1007 |
| 3.2706 | 12.87 | 1528000 | 3.1003 |
| 3.2617 | 12.93 | 1536000 | 3.0978 |
| 3.2617 | 13.0 | 1544000 | 3.1059 |
| 3.2698 | 13.07 | 1552000 | 3.1061 |
| 3.2698 | 13.14 | 1560000 | 3.0986 |
| 3.2721 | 13.2 | 1568000 | 3.1078 |
| 3.2721 | 13.27 | 1576000 | 3.0985 |
| 3.2703 | 13.34 | 1584000 | 3.1060 |
| 3.2703 | 13.41 | 1592000 | 3.0889 |
| 3.2632 | 13.47 | 1600000 | 3.0970 |
| 3.2632 | 13.54 | 1608000 | 3.0893 |
| 3.275 | 13.61 | 1616000 | 3.1048 |
| 3.275 | 13.68 | 1624000 | 3.0975 |
| 3.2692 | 13.74 | 1632000 | 3.1019 |
| 3.2692 | 13.81 | 1640000 | 3.0796 |
| 3.2703 | 13.88 | 1648000 | 3.0986 |
| 3.2703 | 13.95 | 1656000 | 3.1036 |
| 3.2703 | 14.01 | 1664000 | 3.0973 |
| 3.2703 | 14.08 | 1672000 | 3.0910 |
| 3.2621 | 14.15 | 1680000 | 3.0832 |
| 3.2621 | 14.21 | 1688000 | 3.0910 |
| 3.2719 | 14.28 | 1696000 | 3.0927 |
| 3.2719 | 14.35 | 1704000 | 3.0935 |
| 3.2764 | 14.42 | 1712000 | 3.0914 |
| 3.2764 | 14.48 | 1720000 | 3.1064 |
| 3.265 | 14.55 | 1728000 | 3.0977 |
| 3.265 | 14.62 | 1736000 | 3.0933 |
| 3.261 | 14.69 | 1744000 | 3.0969 |
| 3.261 | 14.75 | 1752000 | 3.0911 |
| 3.2757 | 14.82 | 1760000 | 3.0764 |
| 3.2757 | 14.89 | 1768000 | 3.0865 |
| 3.276 | 14.96 | 1776000 | 3.0892 |
| 3.276 | 15.02 | 1784000 | 3.0981 |
| 3.2633 | 15.09 | 1792000 | 3.0920 |
| 3.2633 | 15.16 | 1800000 | 3.0744 |
| 3.2668 | 15.23 | 1808000 | 3.0933 |
| 3.2668 | 15.29 | 1816000 | 3.0907 |
| 3.2687 | 15.36 | 1824000 | 3.0862 |
| 3.2687 | 15.43 | 1832000 | 3.0910 |
| 3.2748 | 15.49 | 1840000 | 3.0950 |
| 3.2748 | 15.56 | 1848000 | 3.0823 |
| 3.2521 | 15.63 | 1856000 | 3.0944 |
| 3.2521 | 15.7 | 1864000 | 3.0819 |
| 3.2621 | 15.76 | 1872000 | 3.0942 |
| 3.2621 | 15.83 | 1880000 | 3.0998 |
| 3.2676 | 15.9 | 1888000 | 3.1061 |
| 3.2676 | 15.97 | 1896000 | 3.0957 |
| 3.2717 | 16.03 | 1904000 | 3.0878 |
| 3.2717 | 16.1 | 1912000 | 3.0802 |
| 3.2631 | 16.17 | 1920000 | 3.0800 |
| 3.2631 | 16.24 | 1928000 | 3.0903 |
| 3.2634 | 16.3 | 1936000 | 3.0924 |
| 3.2634 | 16.37 | 1944000 | 3.0843 |
| 3.2701 | 16.44 | 1952000 | 3.0869 |
| 3.2701 | 16.51 | 1960000 | 3.0776 |
| 3.2665 | 16.57 | 1968000 | 3.0928 |
| 3.2665 | 16.64 | 1976000 | 3.0835 |
| 3.2649 | 16.71 | 1984000 | 3.1013 |
| 3.2649 | 16.78 | 1992000 | 3.0895 |
| 3.2655 | 16.84 | 2000000 | 3.0814 |
| 3.2655 | 16.91 | 2008000 | 3.1003 |
| 3.2657 | 16.98 | 2016000 | 3.0924 |
| 3.2657 | 17.04 | 2024000 | 3.0946 |
| 3.2625 | 17.11 | 2032000 | 3.0956 |
| 3.2625 | 17.18 | 2040000 | 3.0961 |
| 3.2748 | 17.25 | 2048000 | 3.0851 |
| 3.2748 | 17.31 | 2056000 | 3.1006 |
| 3.2767 | 17.38 | 2064000 | 3.0888 |
| 3.2767 | 17.45 | 2072000 | 3.0800 |
| 3.2659 | 17.52 | 2080000 | 3.0859 |
| 3.2659 | 17.58 | 2088000 | 3.0929 |
| 3.2652 | 17.65 | 2096000 | 3.0882 |
| 3.2652 | 17.72 | 2104000 | 3.0930 |
| 3.2627 | 17.79 | 2112000 | 3.0789 |
| 3.2627 | 17.85 | 2120000 | 3.0959 |
| 3.2645 | 17.92 | 2128000 | 3.0989 |
| 3.2645 | 17.99 | 2136000 | 3.0852 |
| 3.2635 | 18.06 | 2144000 | 3.0948 |
| 3.2635 | 18.12 | 2152000 | 3.0890 |
| 3.2684 | 18.19 | 2160000 | 3.0906 |
| 3.2684 | 18.26 | 2168000 | 3.1040 |
| 3.2547 | 18.32 | 2176000 | 3.0923 |
| 3.2547 | 18.39 | 2184000 | 3.0820 |
| 3.2636 | 18.46 | 2192000 | 3.0937 |
| 3.2636 | 18.53 | 2200000 | 3.0951 |
| 3.2702 | 18.59 | 2208000 | 3.0887 |
| 3.2702 | 18.66 | 2216000 | 3.1017 |
| 3.257 | 18.73 | 2224000 | 3.0875 |
| 3.257 | 18.8 | 2232000 | 3.0903 |
| 3.2608 | 18.86 | 2240000 | 3.0945 |
| 3.2608 | 18.93 | 2248000 | 3.0850 |
| 3.2635 | 19.0 | 2256000 | 3.0877 |
| 3.2635 | 19.07 | 2264000 | 3.0873 |
| 3.2673 | 19.13 | 2272000 | 3.0925 |
| 3.2673 | 19.2 | 2280000 | 3.0947 |
| 3.2569 | 19.27 | 2288000 | 3.0901 |
| 3.2569 | 19.34 | 2296000 | 3.0889 |
| 3.2641 | 19.4 | 2304000 | 3.0916 |
| 3.2641 | 19.47 | 2312000 | 3.1022 |
| 3.2735 | 19.54 | 2320000 | 3.0927 |
| 3.2735 | 19.6 | 2328000 | 3.0938 |
| 3.2629 | 19.67 | 2336000 | 3.0892 |
| 3.2629 | 19.74 | 2344000 | 3.0883 |
| 3.2707 | 19.81 | 2352000 | 3.0935 |
| 3.2707 | 19.87 | 2360000 | 3.0909 |
| 3.2595 | 19.94 | 2368000 | 3.0933 |
| 3.2595 | 20.01 | 2376000 | 3.0822 |
| 3.2614 | 20.08 | 2384000 | 3.0932 |
| 3.2614 | 20.14 | 2392000 | 3.0980 |
| 3.2545 | 20.21 | 2400000 | 3.0907 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0