--- base_model: DouglasPontes/2020-Q1-full_tweets tags: - generated_from_trainer model-index: - name: 2020-Q2-full_tweets results: [] --- # 2020-Q2-full_tweets This model is a fine-tuned version of [DouglasPontes/2020-Q1-full_tweets](https://huggingface.co/DouglasPontes/2020-Q1-full_tweets) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.0061 ## 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 | 0.01 | 8000 | 2.1043 | | 2.2608 | 0.02 | 16000 | 2.0934 | | 2.2608 | 0.03 | 24000 | 2.0862 | | 2.2409 | 0.03 | 32000 | 2.0805 | | 2.2409 | 0.04 | 40000 | 2.0793 | | 2.2278 | 0.05 | 48000 | 2.0718 | | 2.2278 | 0.06 | 56000 | 2.0753 | | 2.2059 | 0.07 | 64000 | 2.0668 | | 2.2059 | 0.08 | 72000 | 2.0657 | | 2.1997 | 0.09 | 80000 | 2.0620 | | 2.1997 | 0.1 | 88000 | 2.0553 | | 2.1988 | 0.1 | 96000 | 2.0569 | | 2.1988 | 0.11 | 104000 | 2.0525 | | 2.1861 | 0.12 | 112000 | 2.0556 | | 2.1861 | 0.13 | 120000 | 2.0493 | | 2.1823 | 0.14 | 128000 | 2.0509 | | 2.1823 | 0.15 | 136000 | 2.0461 | | 2.1851 | 0.16 | 144000 | 2.0476 | | 2.1851 | 0.17 | 152000 | 2.0450 | | 2.1862 | 0.17 | 160000 | 2.0469 | | 2.1862 | 0.18 | 168000 | 2.0442 | | 2.1741 | 0.19 | 176000 | 2.0456 | | 2.1741 | 0.2 | 184000 | 2.0442 | | 2.181 | 0.21 | 192000 | 2.0402 | | 2.181 | 0.22 | 200000 | 2.0423 | | 2.1692 | 0.23 | 208000 | 2.0413 | | 2.1692 | 0.24 | 216000 | 2.0448 | | 2.1678 | 0.24 | 224000 | 2.0418 | | 2.1678 | 0.25 | 232000 | 2.0417 | | 2.1756 | 0.26 | 240000 | 2.0342 | | 2.1756 | 0.27 | 248000 | 2.0377 | | 2.1752 | 0.28 | 256000 | 2.0381 | | 2.1752 | 0.29 | 264000 | 2.0354 | | 2.1673 | 0.3 | 272000 | 2.0381 | | 2.1673 | 0.31 | 280000 | 2.0375 | | 2.1585 | 0.31 | 288000 | 2.0336 | | 2.1585 | 0.32 | 296000 | 2.0344 | | 2.1703 | 0.33 | 304000 | 2.0348 | | 2.1703 | 0.34 | 312000 | 2.0330 | | 2.1667 | 0.35 | 320000 | 2.0352 | | 2.1667 | 0.36 | 328000 | 2.0359 | | 2.1649 | 0.37 | 336000 | 2.0317 | | 2.1649 | 0.38 | 344000 | 2.0314 | | 2.1564 | 0.38 | 352000 | 2.0306 | | 2.1564 | 0.39 | 360000 | 2.0299 | | 2.161 | 0.4 | 368000 | 2.0317 | | 2.161 | 0.41 | 376000 | 2.0325 | | 2.1551 | 0.42 | 384000 | 2.0274 | | 2.1551 | 0.43 | 392000 | 2.0282 | | 2.1602 | 0.44 | 400000 | 2.0301 | | 2.1602 | 0.45 | 408000 | 2.0303 | | 2.1581 | 0.45 | 416000 | 2.0260 | | 2.1581 | 0.46 | 424000 | 2.0248 | | 2.1494 | 0.47 | 432000 | 2.0265 | | 2.1494 | 0.48 | 440000 | 2.0247 | | 2.1508 | 0.49 | 448000 | 2.0231 | | 2.1508 | 0.5 | 456000 | 2.0276 | | 2.153 | 0.51 | 464000 | 2.0276 | | 2.153 | 0.51 | 472000 | 2.0242 | | 2.1489 | 0.52 | 480000 | 2.0259 | | 2.1489 | 0.53 | 488000 | 2.0257 | | 2.1468 | 0.54 | 496000 | 2.0275 | | 2.1468 | 0.55 | 504000 | 2.0303 | | 2.1446 | 0.56 | 512000 | 2.0248 | | 2.1446 | 0.57 | 520000 | 2.0286 | | 2.1409 | 0.58 | 528000 | 2.0211 | | 2.1409 | 0.58 | 536000 | 2.0204 | | 2.1536 | 0.59 | 544000 | 2.0199 | | 2.1536 | 0.6 | 552000 | 2.0281 | | 2.1416 | 0.61 | 560000 | 2.0237 | | 2.1416 | 0.62 | 568000 | 2.0231 | | 2.1502 | 0.63 | 576000 | 2.0205 | | 2.1502 | 0.64 | 584000 | 2.0217 | | 2.1424 | 0.65 | 592000 | 2.0242 | | 2.1424 | 0.65 | 600000 | 2.0238 | | 2.1469 | 0.66 | 608000 | 2.0192 | | 2.1469 | 0.67 | 616000 | 2.0249 | | 2.145 | 0.68 | 624000 | 2.0196 | | 2.145 | 0.69 | 632000 | 2.0224 | | 2.1503 | 0.7 | 640000 | 2.0216 | | 2.1503 | 0.71 | 648000 | 2.0228 | | 2.1355 | 0.72 | 656000 | 2.0197 | | 2.1355 | 0.72 | 664000 | 2.0240 | | 2.1392 | 0.73 | 672000 | 2.0232 | | 2.1392 | 0.74 | 680000 | 2.0209 | | 2.1378 | 0.75 | 688000 | 2.0219 | | 2.1378 | 0.76 | 696000 | 2.0192 | | 2.1446 | 0.77 | 704000 | 2.0195 | | 2.1446 | 0.78 | 712000 | 2.0197 | | 2.1351 | 0.79 | 720000 | 2.0184 | | 2.1351 | 0.79 | 728000 | 2.0162 | | 2.1437 | 0.8 | 736000 | 2.0151 | | 2.1437 | 0.81 | 744000 | 2.0202 | | 2.1249 | 0.82 | 752000 | 2.0169 | | 2.1249 | 0.83 | 760000 | 2.0189 | | 2.1355 | 0.84 | 768000 | 2.0221 | | 2.1355 | 0.85 | 776000 | 2.0194 | | 2.1387 | 0.86 | 784000 | 2.0189 | | 2.1387 | 0.86 | 792000 | 2.0165 | | 2.1334 | 0.87 | 800000 | 2.0169 | | 2.1334 | 0.88 | 808000 | 2.0189 | | 2.137 | 0.89 | 816000 | 2.0162 | | 2.137 | 0.9 | 824000 | 2.0168 | | 2.1331 | 0.91 | 832000 | 2.0193 | | 2.1331 | 0.92 | 840000 | 2.0166 | | 2.1293 | 0.93 | 848000 | 2.0137 | | 2.1293 | 0.93 | 856000 | 2.0183 | | 2.1358 | 0.94 | 864000 | 2.0184 | | 2.1358 | 0.95 | 872000 | 2.0171 | | 2.1296 | 0.96 | 880000 | 2.0179 | | 2.1296 | 0.97 | 888000 | 2.0152 | | 2.1319 | 0.98 | 896000 | 2.0174 | | 2.1319 | 0.99 | 904000 | 2.0206 | | 2.1344 | 1.0 | 912000 | 2.0179 | | 2.1344 | 1.0 | 920000 | 2.0154 | | 2.1352 | 1.01 | 928000 | 2.0185 | | 2.1352 | 1.02 | 936000 | 2.0170 | | 2.1336 | 1.03 | 944000 | 2.0164 | | 2.1336 | 1.04 | 952000 | 2.0137 | | 2.1315 | 1.05 | 960000 | 2.0176 | | 2.1315 | 1.06 | 968000 | 2.0155 | | 2.1255 | 1.06 | 976000 | 2.0145 | | 2.1255 | 1.07 | 984000 | 2.0233 | | 2.1249 | 1.08 | 992000 | 2.0148 | | 2.1249 | 1.09 | 1000000 | 2.0162 | | 2.123 | 1.1 | 1008000 | 2.0174 | | 2.123 | 1.11 | 1016000 | 2.0150 | | 2.1263 | 1.12 | 1024000 | 2.0161 | | 2.1263 | 1.13 | 1032000 | 2.0129 | | 2.1232 | 1.13 | 1040000 | 2.0167 | | 2.1232 | 1.14 | 1048000 | 2.0125 | | 2.1168 | 1.15 | 1056000 | 2.0113 | | 2.1168 | 1.16 | 1064000 | 2.0136 | | 2.1307 | 1.17 | 1072000 | 2.0143 | | 2.1307 | 1.18 | 1080000 | 2.0166 | | 2.1336 | 1.19 | 1088000 | 2.0103 | | 2.1336 | 1.2 | 1096000 | 2.0130 | | 2.1227 | 1.2 | 1104000 | 2.0125 | | 2.1227 | 1.21 | 1112000 | 2.0183 | | 2.1223 | 1.22 | 1120000 | 2.0148 | | 2.1223 | 1.23 | 1128000 | 2.0147 | | 2.1289 | 1.24 | 1136000 | 2.0109 | | 2.1289 | 1.25 | 1144000 | 2.0164 | | 2.1278 | 1.26 | 1152000 | 2.0163 | | 2.1278 | 1.27 | 1160000 | 2.0121 | | 2.1261 | 1.27 | 1168000 | 2.0113 | | 2.1261 | 1.28 | 1176000 | 2.0137 | | 2.126 | 1.29 | 1184000 | 2.0152 | | 2.126 | 1.3 | 1192000 | 2.0104 | | 2.1235 | 1.31 | 1200000 | 2.0132 | | 2.1235 | 1.32 | 1208000 | 2.0114 | | 2.1229 | 1.33 | 1216000 | 2.0105 | | 2.1229 | 1.34 | 1224000 | 2.0131 | | 2.1213 | 1.34 | 1232000 | 2.0141 | | 2.1213 | 1.35 | 1240000 | 2.0109 | | 2.1185 | 1.36 | 1248000 | 2.0129 | | 2.1185 | 1.37 | 1256000 | 2.0110 | | 2.131 | 1.38 | 1264000 | 2.0123 | | 2.131 | 1.39 | 1272000 | 2.0105 | | 2.1141 | 1.4 | 1280000 | 2.0104 | | 2.1141 | 1.41 | 1288000 | 2.0150 | | 2.1219 | 1.41 | 1296000 | 2.0161 | | 2.1219 | 1.42 | 1304000 | 2.0093 | | 2.1203 | 1.43 | 1312000 | 2.0104 | | 2.1203 | 1.44 | 1320000 | 2.0144 | | 2.1264 | 1.45 | 1328000 | 2.0085 | | 2.1264 | 1.46 | 1336000 | 2.0119 | | 2.1194 | 1.47 | 1344000 | 2.0118 | | 2.1194 | 1.48 | 1352000 | 2.0110 | | 2.117 | 1.48 | 1360000 | 2.0147 | | 2.117 | 1.49 | 1368000 | 2.0135 | | 2.1311 | 1.5 | 1376000 | 2.0077 | | 2.1311 | 1.51 | 1384000 | 2.0066 | | 2.1215 | 1.52 | 1392000 | 2.0089 | | 2.1215 | 1.53 | 1400000 | 2.0118 | | 2.1185 | 1.54 | 1408000 | 2.0105 | | 2.1185 | 1.54 | 1416000 | 2.0123 | | 2.1284 | 1.55 | 1424000 | 2.0134 | | 2.1284 | 1.56 | 1432000 | 2.0093 | | 2.1174 | 1.57 | 1440000 | 2.0102 | | 2.1174 | 1.58 | 1448000 | 2.0076 | | 2.1108 | 1.59 | 1456000 | 2.0074 | | 2.1108 | 1.6 | 1464000 | 2.0071 | | 2.1252 | 1.61 | 1472000 | 2.0092 | | 2.1252 | 1.61 | 1480000 | 2.0080 | | 2.121 | 1.62 | 1488000 | 2.0053 | | 2.121 | 1.63 | 1496000 | 2.0072 | | 2.1178 | 1.64 | 1504000 | 2.0059 | | 2.1178 | 1.65 | 1512000 | 2.0084 | | 2.1154 | 1.66 | 1520000 | 2.0106 | | 2.1154 | 1.67 | 1528000 | 2.0117 | | 2.1214 | 1.68 | 1536000 | 2.0070 | | 2.1214 | 1.68 | 1544000 | 2.0079 | | 2.1175 | 1.69 | 1552000 | 2.0102 | | 2.1175 | 1.7 | 1560000 | 2.0097 | | 2.1206 | 1.71 | 1568000 | 2.0092 | | 2.1206 | 1.72 | 1576000 | 2.0055 | | 2.1302 | 1.73 | 1584000 | 2.0085 | | 2.1302 | 1.74 | 1592000 | 2.0110 | | 2.1177 | 1.75 | 1600000 | 2.0065 | | 2.1177 | 1.75 | 1608000 | 2.0132 | | 2.1101 | 1.76 | 1616000 | 2.0086 | | 2.1101 | 1.77 | 1624000 | 2.0077 | | 2.1194 | 1.78 | 1632000 | 2.0081 | | 2.1194 | 1.79 | 1640000 | 2.0088 | | 2.1167 | 1.8 | 1648000 | 2.0022 | | 2.1167 | 1.81 | 1656000 | 2.0077 | | 2.1083 | 1.82 | 1664000 | 2.0066 | | 2.1083 | 1.82 | 1672000 | 2.0137 | | 2.1232 | 1.83 | 1680000 | 2.0067 | | 2.1232 | 1.84 | 1688000 | 2.0039 | | 2.1212 | 1.85 | 1696000 | 2.0090 | | 2.1212 | 1.86 | 1704000 | 2.0079 | | 2.1246 | 1.87 | 1712000 | 2.0083 | | 2.1246 | 1.88 | 1720000 | 2.0039 | | 2.1129 | 1.89 | 1728000 | 2.0069 | | 2.1129 | 1.89 | 1736000 | 2.0079 | | 2.1209 | 1.9 | 1744000 | 2.0058 | | 2.1209 | 1.91 | 1752000 | 2.0072 | | 2.1209 | 1.92 | 1760000 | 2.0068 | | 2.1209 | 1.93 | 1768000 | 2.0079 | | 2.1184 | 1.94 | 1776000 | 2.0036 | | 2.1184 | 1.95 | 1784000 | 2.0065 | | 2.1065 | 1.96 | 1792000 | 2.0077 | | 2.1065 | 1.96 | 1800000 | 2.0062 | | 2.109 | 1.97 | 1808000 | 2.0090 | | 2.109 | 1.98 | 1816000 | 2.0124 | | 2.1081 | 1.99 | 1824000 | 2.0066 | | 2.1081 | 2.0 | 1832000 | 2.0081 | | 2.1151 | 2.01 | 1840000 | 2.0085 | | 2.1151 | 2.02 | 1848000 | 2.0054 | | 2.1178 | 2.03 | 1856000 | 2.0058 | | 2.1178 | 2.03 | 1864000 | 2.0048 | | 2.1035 | 2.04 | 1872000 | 2.0040 | | 2.1035 | 2.05 | 1880000 | 2.0059 | | 2.1197 | 2.06 | 1888000 | 2.0071 | | 2.1197 | 2.07 | 1896000 | 2.0057 | | 2.1143 | 2.08 | 1904000 | 2.0059 | | 2.1143 | 2.09 | 1912000 | 2.0043 | | 2.1082 | 2.09 | 1920000 | 2.0068 | | 2.1082 | 2.1 | 1928000 | 2.0057 | | 2.1202 | 2.11 | 1936000 | 2.0072 | | 2.1202 | 2.12 | 1944000 | 2.0057 | | 2.1138 | 2.13 | 1952000 | 2.0051 | | 2.1138 | 2.14 | 1960000 | 2.0085 | | 2.1082 | 2.15 | 1968000 | 2.0076 | | 2.1082 | 2.16 | 1976000 | 2.0077 | | 2.1084 | 2.16 | 1984000 | 2.0020 | | 2.1084 | 2.17 | 1992000 | 2.0050 | | 2.1151 | 2.18 | 2000000 | 2.0066 | | 2.1151 | 2.19 | 2008000 | 2.0031 | | 2.1141 | 2.2 | 2016000 | 2.0128 | | 2.1141 | 2.21 | 2024000 | 2.0022 | | 2.1129 | 2.22 | 2032000 | 2.0065 | | 2.1129 | 2.23 | 2040000 | 2.0054 | | 2.1164 | 2.23 | 2048000 | 2.0039 | | 2.1164 | 2.24 | 2056000 | 2.0031 | | 2.1121 | 2.25 | 2064000 | 2.0101 | | 2.1121 | 2.26 | 2072000 | 2.0099 | | 2.1071 | 2.27 | 2080000 | 2.0042 | | 2.1071 | 2.28 | 2088000 | 2.0030 | | 2.1094 | 2.29 | 2096000 | 2.0048 | | 2.1094 | 2.3 | 2104000 | 2.0046 | | 2.1017 | 2.3 | 2112000 | 2.0039 | | 2.1017 | 2.31 | 2120000 | 2.0011 | | 2.1124 | 2.32 | 2128000 | 2.0071 | | 2.1124 | 2.33 | 2136000 | 2.0061 | | 2.1064 | 2.34 | 2144000 | 2.0040 | | 2.1064 | 2.35 | 2152000 | 2.0075 | | 2.115 | 2.36 | 2160000 | 2.0026 | | 2.115 | 2.37 | 2168000 | 2.0068 | | 2.114 | 2.37 | 2176000 | 2.0066 | | 2.114 | 2.38 | 2184000 | 2.0080 | | 2.1171 | 2.39 | 2192000 | 2.0032 | | 2.1171 | 2.4 | 2200000 | 2.0036 | | 2.1119 | 2.41 | 2208000 | 2.0048 | | 2.1119 | 2.42 | 2216000 | 2.0059 | | 2.1097 | 2.43 | 2224000 | 2.0058 | | 2.1097 | 2.44 | 2232000 | 2.0049 | | 2.1091 | 2.44 | 2240000 | 2.0058 | | 2.1091 | 2.45 | 2248000 | 2.0032 | | 2.1107 | 2.46 | 2256000 | 2.0077 | | 2.1107 | 2.47 | 2264000 | 2.0032 | | 2.1126 | 2.48 | 2272000 | 2.0055 | | 2.1126 | 2.49 | 2280000 | 2.0026 | | 2.1173 | 2.5 | 2288000 | 2.0062 | | 2.1173 | 2.51 | 2296000 | 2.0039 | | 2.114 | 2.51 | 2304000 | 2.0064 | | 2.114 | 2.52 | 2312000 | 2.0113 | | 2.1131 | 2.53 | 2320000 | 2.0065 | | 2.1131 | 2.54 | 2328000 | 2.0098 | | 2.1045 | 2.55 | 2336000 | 2.0061 | | 2.1045 | 2.56 | 2344000 | 2.0066 | | 2.1144 | 2.57 | 2352000 | 2.0060 | | 2.1144 | 2.57 | 2360000 | 2.0059 | | 2.1086 | 2.58 | 2368000 | 2.0039 | | 2.1086 | 2.59 | 2376000 | 2.0076 | | 2.1058 | 2.6 | 2384000 | 2.0036 | | 2.1058 | 2.61 | 2392000 | 2.0077 | | 2.1112 | 2.62 | 2400000 | 2.0000 | ### Framework versions - Transformers 4.35.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.14.5 - Tokenizers 0.14.0