2020-Q2-full_tweets

DouglasPontes/2020-Q2-full_tweets

2020-Q2-full_tweets is a fill-mask model from DouglasPontes. Use it when you need the model to fill a missing word. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Fill-Mask
Library: transformers
Model type: roberta
Access: Public
Created: Jan 7, 2024
Updated: Jan 12, 2024
SHA: 937feb1d

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Base models

DouglasPontes/2020-Q1-full_tweets

Model card

From the Hugging Face model README

2020-Q2-full_tweets

This model is a fine-tuned version of 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

Task: Fill-Mask
Library: transformers
Type: roberta
Created: Jan 7, 2024
Updated: Jan 12, 2024