--- license: mit base_model: cardiffnlp/twitter-roberta-base-2019-90m tags: - generated_from_trainer model-index: - name: 2020-Q2-75p-filtered results: [] --- # 2020-Q2-75p-filtered This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-2019-90m](https://huggingface.co/cardiffnlp/twitter-roberta-base-2019-90m) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 3.0187 ## 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: 1e-05 - 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 - lr_scheduler_warmup_steps: 1400 - training_steps: 2400000 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:-------:|:---------------:| | No log | 0.07 | 8000 | 3.1520 | | 3.3704 | 0.13 | 16000 | 3.1286 | | 3.3704 | 0.2 | 24000 | 3.1079 | | 3.2908 | 0.27 | 32000 | 3.0845 | | 3.2908 | 0.34 | 40000 | 3.0868 | | 3.2742 | 0.4 | 48000 | 3.0768 | | 3.2742 | 0.47 | 56000 | 3.0706 | | 3.2579 | 0.54 | 64000 | 3.0621 | | 3.2579 | 0.61 | 72000 | 3.0659 | | 3.2448 | 0.67 | 80000 | 3.0457 | | 3.2448 | 0.74 | 88000 | 3.0554 | | 3.2416 | 0.81 | 96000 | 3.0335 | | 3.2416 | 0.88 | 104000 | 3.0321 | | 3.23 | 0.94 | 112000 | 3.0137 | | 3.23 | 1.01 | 120000 | 3.0061 | | 3.2084 | 1.08 | 128000 | 3.0251 | | 3.2084 | 1.15 | 136000 | 3.0092 | | 3.2055 | 1.21 | 144000 | 3.0043 | | 3.2055 | 1.28 | 152000 | 3.0055 | | 3.2026 | 1.35 | 160000 | 3.0066 | | 3.2026 | 1.41 | 168000 | 3.0125 | | 3.2069 | 1.48 | 176000 | 3.0032 | | 3.2069 | 1.55 | 184000 | 2.9959 | | 3.1904 | 1.62 | 192000 | 2.9960 | | 3.1904 | 1.68 | 200000 | 3.0038 | | 3.1989 | 1.75 | 208000 | 3.0016 | | 3.1989 | 1.82 | 216000 | 3.0049 | | 3.2113 | 1.89 | 224000 | 3.0086 | | 3.2113 | 1.95 | 232000 | 3.0104 | | 3.217 | 2.02 | 240000 | 3.0166 | | 3.217 | 2.09 | 248000 | 3.0139 | | 3.2029 | 2.16 | 256000 | 3.0217 | | 3.2029 | 2.22 | 264000 | 3.0238 | | 3.2226 | 2.29 | 272000 | 3.0234 | | 3.2226 | 2.36 | 280000 | 3.0216 | | 3.2199 | 2.43 | 288000 | 3.0175 | | 3.2199 | 2.49 | 296000 | 3.0365 | | 3.2254 | 2.56 | 304000 | 3.0282 | | 3.2254 | 2.63 | 312000 | 3.0228 | | 3.2349 | 2.7 | 320000 | 3.0205 | | 3.2349 | 2.76 | 328000 | 3.0406 | | 3.2424 | 2.83 | 336000 | 3.0307 | | 3.2424 | 2.9 | 344000 | 3.0413 | | 3.2347 | 2.96 | 352000 | 3.0401 | | 3.2347 | 3.03 | 360000 | 3.0520 | | 3.2476 | 3.1 | 368000 | 3.0489 | | 3.2476 | 3.17 | 376000 | 3.0521 | | 3.2506 | 3.23 | 384000 | 3.0685 | | 3.2506 | 3.3 | 392000 | 3.0546 | | 3.2547 | 3.37 | 400000 | 3.0542 | | 3.2547 | 3.44 | 408000 | 3.0537 | | 3.2519 | 3.5 | 416000 | 3.0588 | | 3.2519 | 3.57 | 424000 | 3.0729 | | 3.2679 | 3.64 | 432000 | 3.0842 | | 3.2679 | 3.71 | 440000 | 3.0685 | | 3.2656 | 3.77 | 448000 | 3.0942 | | 3.2656 | 3.84 | 456000 | 3.0942 | | 3.2908 | 3.91 | 464000 | 3.0918 | | 3.2908 | 3.98 | 472000 | 3.0922 | | 3.2944 | 4.04 | 480000 | 3.1093 | | 3.2944 | 4.11 | 488000 | 3.1158 | | 3.2917 | 4.18 | 496000 | 3.0997 | | 3.2917 | 4.24 | 504000 | 3.1111 | | 3.2916 | 4.31 | 512000 | 3.1133 | | 3.2916 | 4.38 | 520000 | 3.1129 | | 3.2836 | 4.45 | 528000 | 3.1134 | | 3.2836 | 4.51 | 536000 | 3.1058 | | 3.3068 | 4.58 | 544000 | 3.1211 | | 3.3068 | 4.65 | 552000 | 3.0946 | | 3.3026 | 4.72 | 560000 | 3.1079 | | 3.3026 | 4.78 | 568000 | 3.1202 | | 3.3078 | 4.85 | 576000 | 3.1155 | | 3.3078 | 4.92 | 584000 | 3.1254 | | 3.3168 | 4.99 | 592000 | 3.1279 | | 3.3168 | 5.05 | 600000 | 3.1179 | | 3.3113 | 5.12 | 608000 | 3.1277 | | 3.3113 | 5.19 | 616000 | 3.1334 | | 3.3102 | 5.26 | 624000 | 3.1233 | | 3.3102 | 5.32 | 632000 | 3.1274 | | 3.3235 | 5.39 | 640000 | 3.1434 | | 3.3235 | 5.46 | 648000 | 3.1368 | | 3.331 | 5.53 | 656000 | 3.1591 | | 3.331 | 5.59 | 664000 | 3.1546 | | 3.3308 | 5.66 | 672000 | 3.1663 | | 3.3308 | 5.73 | 680000 | 3.1535 | | 3.3396 | 5.79 | 688000 | 3.1558 | | 3.3396 | 5.86 | 696000 | 3.1698 | | 3.3558 | 5.93 | 704000 | 3.1651 | | 3.3558 | 6.0 | 712000 | 3.1706 | | 3.3474 | 6.06 | 720000 | 3.1942 | | 3.3474 | 6.13 | 728000 | 3.1705 | | 3.3513 | 6.2 | 736000 | 3.1834 | | 3.3513 | 6.27 | 744000 | 3.1810 | | 3.362 | 6.33 | 752000 | 3.1723 | | 3.362 | 6.4 | 760000 | 3.1827 | | 3.3694 | 6.47 | 768000 | 3.1937 | | 3.3694 | 6.54 | 776000 | 3.2004 | | 3.378 | 6.6 | 784000 | 3.2023 | | 3.378 | 6.67 | 792000 | 3.1936 | | 3.3703 | 6.74 | 800000 | 3.1948 | | 3.3703 | 6.81 | 808000 | 3.2082 | | 3.3838 | 6.87 | 816000 | 3.1974 | | 3.3838 | 6.94 | 824000 | 3.2029 | | 3.3871 | 7.01 | 832000 | 3.2160 | | 3.3871 | 7.07 | 840000 | 3.2198 | | 3.3839 | 7.14 | 848000 | 3.2190 | | 3.3839 | 7.21 | 856000 | 3.2204 | | 3.389 | 7.28 | 864000 | 3.2188 | | 3.389 | 7.34 | 872000 | 3.2246 | | 3.398 | 7.41 | 880000 | 3.2333 | | 3.398 | 7.48 | 888000 | 3.2168 | | 3.4001 | 7.55 | 896000 | 3.2311 | | 3.4001 | 7.61 | 904000 | 3.2390 | | 3.4255 | 7.68 | 912000 | 3.2447 | | 3.4255 | 7.75 | 920000 | 3.2546 | | 3.4218 | 7.82 | 928000 | 3.2510 | | 3.4218 | 7.88 | 936000 | 3.2433 | | 3.4326 | 7.95 | 944000 | 3.2509 | | 3.4326 | 8.02 | 952000 | 3.2573 | | 3.4268 | 8.09 | 960000 | 3.2499 | | 3.4268 | 8.15 | 968000 | 3.2704 | | 3.4165 | 8.22 | 976000 | 3.2579 | | 3.4165 | 8.29 | 984000 | 3.2669 | | 3.4425 | 8.36 | 992000 | 3.2723 | | 3.4425 | 8.42 | 1000000 | 3.2718 | | 3.4433 | 8.49 | 1008000 | 3.2655 | | 3.4433 | 8.56 | 1016000 | 3.2794 | | 3.4437 | 8.62 | 1024000 | 3.2808 | | 3.4437 | 8.69 | 1032000 | 3.2731 | | 3.4499 | 8.76 | 1040000 | 3.2785 | | 3.4499 | 8.83 | 1048000 | 3.2823 | | 3.4593 | 8.89 | 1056000 | 3.2844 | | 3.4593 | 8.96 | 1064000 | 3.2877 | | 3.4481 | 9.03 | 1072000 | 3.2969 | | 3.4481 | 9.1 | 1080000 | 3.2870 | | 3.4542 | 9.16 | 1088000 | 3.2946 | | 3.4542 | 9.23 | 1096000 | 3.2901 | | 3.4547 | 9.3 | 1104000 | 3.2813 | | 3.4547 | 9.37 | 1112000 | 3.2910 | | 3.4618 | 9.43 | 1120000 | 3.2978 | | 3.4618 | 9.5 | 1128000 | 3.3055 | | 3.46 | 9.57 | 1136000 | 3.2885 | | 3.46 | 9.64 | 1144000 | 3.2871 | | 3.4572 | 9.7 | 1152000 | 3.2905 | | 3.4572 | 9.77 | 1160000 | 3.3006 | | 3.4597 | 9.84 | 1168000 | 3.3081 | | 3.4597 | 9.9 | 1176000 | 3.3031 | | 3.4651 | 9.97 | 1184000 | 3.2883 | | 3.4651 | 10.04 | 1192000 | 3.3189 | | 3.4571 | 10.11 | 1200000 | 3.2978 | | 3.4571 | 10.17 | 1208000 | 3.3091 | | 3.4567 | 10.24 | 1216000 | 3.2755 | | 3.4567 | 10.31 | 1224000 | 3.2968 | | 3.4584 | 10.38 | 1232000 | 3.2991 | | 3.4584 | 10.44 | 1240000 | 3.2818 | | 3.4459 | 10.51 | 1248000 | 3.2823 | | 3.4459 | 10.58 | 1256000 | 3.2800 | | 3.4474 | 10.65 | 1264000 | 3.2856 | | 3.4474 | 10.71 | 1272000 | 3.2845 | | 3.4383 | 10.78 | 1280000 | 3.2804 | | 3.4383 | 10.85 | 1288000 | 3.2707 | | 3.4496 | 10.92 | 1296000 | 3.2824 | | 3.4496 | 10.98 | 1304000 | 3.2765 | | 3.4411 | 11.05 | 1312000 | 3.2838 | | 3.4411 | 11.12 | 1320000 | 3.2839 | | 3.4305 | 11.19 | 1328000 | 3.2748 | | 3.4305 | 11.25 | 1336000 | 3.2821 | | 3.4258 | 11.32 | 1344000 | 3.2746 | | 3.4258 | 11.39 | 1352000 | 3.2861 | | 3.4227 | 11.45 | 1360000 | 3.2710 | | 3.4227 | 11.52 | 1368000 | 3.2788 | | 3.4319 | 11.59 | 1376000 | 3.2794 | | 3.4319 | 11.66 | 1384000 | 3.2766 | | 3.436 | 11.72 | 1392000 | 3.2924 | | 3.436 | 11.79 | 1400000 | 3.2812 | | 3.4368 | 11.86 | 1408000 | 3.2851 | | 3.4368 | 11.93 | 1416000 | 3.2822 | | 3.4346 | 11.99 | 1424000 | 3.2657 | | 3.4346 | 12.06 | 1432000 | 3.2748 | | 3.4265 | 12.13 | 1440000 | 3.2685 | | 3.4265 | 12.2 | 1448000 | 3.2947 | | 3.4306 | 12.26 | 1456000 | 3.2841 | | 3.4306 | 12.33 | 1464000 | 3.2748 | | 3.4254 | 12.4 | 1472000 | 3.2794 | | 3.4254 | 12.47 | 1480000 | 3.2774 | | 3.4353 | 12.53 | 1488000 | 3.2726 | | 3.4353 | 12.6 | 1496000 | 3.2763 | | 3.4358 | 12.67 | 1504000 | 3.2659 | | 3.4358 | 12.73 | 1512000 | 3.2710 | | 3.4182 | 12.8 | 1520000 | 3.2777 | | 3.4182 | 12.87 | 1528000 | 3.2824 | | 3.4384 | 12.94 | 1536000 | 3.2887 | | 3.4384 | 13.0 | 1544000 | 3.2667 | | 3.4287 | 13.07 | 1552000 | 3.2713 | | 3.4287 | 13.14 | 1560000 | 3.2640 | | 3.4181 | 13.21 | 1568000 | 3.2607 | | 3.4181 | 13.27 | 1576000 | 3.2643 | | 3.4173 | 13.34 | 1584000 | 3.2630 | | 3.4173 | 13.41 | 1592000 | 3.2572 | | 3.4214 | 13.48 | 1600000 | 3.2728 | | 3.4214 | 13.54 | 1608000 | 3.2822 | | 3.4223 | 13.61 | 1616000 | 3.2704 | | 3.4223 | 13.68 | 1624000 | 3.2634 | | 3.417 | 13.75 | 1632000 | 3.2691 | | 3.417 | 13.81 | 1640000 | 3.2550 | | 3.4146 | 13.88 | 1648000 | 3.2529 | | 3.4146 | 13.95 | 1656000 | 3.2713 | | 3.4186 | 14.02 | 1664000 | 3.2672 | | 3.4186 | 14.08 | 1672000 | 3.2542 | | 3.4082 | 14.15 | 1680000 | 3.2576 | | 3.4082 | 14.22 | 1688000 | 3.2680 | | 3.4186 | 14.28 | 1696000 | 3.2667 | | 3.4186 | 14.35 | 1704000 | 3.2694 | | 3.4131 | 14.42 | 1712000 | 3.2606 | | 3.4131 | 14.49 | 1720000 | 3.2622 | | 3.4239 | 14.55 | 1728000 | 3.2678 | | 3.4239 | 14.62 | 1736000 | 3.2708 | | 3.4197 | 14.69 | 1744000 | 3.2622 | | 3.4197 | 14.76 | 1752000 | 3.2605 | | 3.4073 | 14.82 | 1760000 | 3.2647 | | 3.4073 | 14.89 | 1768000 | 3.2619 | | 3.4167 | 14.96 | 1776000 | 3.2816 | | 3.4167 | 15.03 | 1784000 | 3.2603 | | 3.413 | 15.09 | 1792000 | 3.2661 | | 3.413 | 15.16 | 1800000 | 3.2589 | | 3.4117 | 15.23 | 1808000 | 3.2688 | | 3.4117 | 15.3 | 1816000 | 3.2678 | | 3.4103 | 15.36 | 1824000 | 3.2661 | | 3.4103 | 15.43 | 1832000 | 3.2705 | | 3.4074 | 15.5 | 1840000 | 3.2670 | | 3.4074 | 15.56 | 1848000 | 3.2619 | | 3.4167 | 15.63 | 1856000 | 3.2624 | | 3.4167 | 15.7 | 1864000 | 3.2552 | | 3.4195 | 15.77 | 1872000 | 3.2503 | | 3.4195 | 15.83 | 1880000 | 3.2606 | | 3.4091 | 15.9 | 1888000 | 3.2812 | | 3.4091 | 15.97 | 1896000 | 3.2837 | | 3.4116 | 16.04 | 1904000 | 3.2658 | | 3.4116 | 16.1 | 1912000 | 3.2676 | | 3.4183 | 16.17 | 1920000 | 3.2770 | | 3.4183 | 16.24 | 1928000 | 3.2756 | | 3.4177 | 16.31 | 1936000 | 3.2876 | | 3.4177 | 16.37 | 1944000 | 3.2612 | | 3.4226 | 16.44 | 1952000 | 3.2748 | | 3.4226 | 16.51 | 1960000 | 3.2679 | | 3.4154 | 16.58 | 1968000 | 3.2659 | | 3.4154 | 16.64 | 1976000 | 3.2689 | | 3.4199 | 16.71 | 1984000 | 3.2701 | | 3.4199 | 16.78 | 1992000 | 3.2564 | | 3.4166 | 16.85 | 2000000 | 3.2714 | | 3.4166 | 16.91 | 2008000 | 3.2738 | | 3.4054 | 16.98 | 2016000 | 3.2633 | | 3.4054 | 17.05 | 2024000 | 3.2574 | | 3.4022 | 17.11 | 2032000 | 3.2637 | | 3.4022 | 17.18 | 2040000 | 3.2688 | | 3.408 | 17.25 | 2048000 | 3.2667 | | 3.408 | 17.32 | 2056000 | 3.2578 | | 3.4065 | 17.38 | 2064000 | 3.2605 | | 3.4065 | 17.45 | 2072000 | 3.2768 | | 3.4105 | 17.52 | 2080000 | 3.2569 | | 3.4105 | 17.59 | 2088000 | 3.2519 | | 3.4011 | 17.65 | 2096000 | 3.2555 | | 3.4011 | 17.72 | 2104000 | 3.2488 | | 3.4078 | 17.79 | 2112000 | 3.2516 | | 3.4078 | 17.86 | 2120000 | 3.2527 | | 3.4105 | 17.92 | 2128000 | 3.2561 | | 3.4105 | 17.99 | 2136000 | 3.2580 | | 3.4054 | 18.06 | 2144000 | 3.2453 | | 3.4054 | 18.13 | 2152000 | 3.2426 | | 3.3937 | 18.19 | 2160000 | 3.2517 | | 3.3937 | 18.26 | 2168000 | 3.2446 | | 3.4001 | 18.33 | 2176000 | 3.2449 | | 3.4001 | 18.39 | 2184000 | 3.2527 | | 3.413 | 18.46 | 2192000 | 3.2557 | | 3.413 | 18.53 | 2200000 | 3.2483 | | 3.3882 | 18.6 | 2208000 | 3.2520 | | 3.3882 | 18.66 | 2216000 | 3.2354 | | 3.3974 | 18.73 | 2224000 | 3.2540 | | 3.3974 | 18.8 | 2232000 | 3.2426 | | 3.3864 | 18.87 | 2240000 | 3.2341 | | 3.3864 | 18.93 | 2248000 | 3.2408 | | 3.3896 | 19.0 | 2256000 | 3.2342 | | 3.3896 | 19.07 | 2264000 | 3.2415 | | 3.3845 | 19.14 | 2272000 | 3.2445 | | 3.3845 | 19.2 | 2280000 | 3.2422 | | 3.3916 | 19.27 | 2288000 | 3.2379 | | 3.3916 | 19.34 | 2296000 | 3.2411 | | 3.3919 | 19.41 | 2304000 | 3.2429 | | 3.3919 | 19.47 | 2312000 | 3.2372 | | 3.39 | 19.54 | 2320000 | 3.2380 | | 3.39 | 19.61 | 2328000 | 3.2353 | | 3.3905 | 19.68 | 2336000 | 3.2327 | | 3.3905 | 19.74 | 2344000 | 3.2494 | | 3.3826 | 19.81 | 2352000 | 3.2369 | | 3.3826 | 19.88 | 2360000 | 3.2390 | | 3.3935 | 19.94 | 2368000 | 3.2415 | | 3.3935 | 20.01 | 2376000 | 3.2486 | | 3.3846 | 20.08 | 2384000 | 3.2354 | | 3.3846 | 20.15 | 2392000 | 3.2466 | | 3.3875 | 20.21 | 2400000 | 3.2425 | ### Framework versions - Transformers 4.35.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.14.5 - Tokenizers 0.14.0