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DouglasPontes/
2020-Q2-full_tweets

Name: 2020-Q2-full_tweets
Availability: InStock

generated_from_trainer

DouglasPontes/2020-Q1-full_tweets

finetune

autotrain_compatible

endpoints_compatible

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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

DouglasPontes/2020-Q2-full_tweets

2020-Q2-full_tweets

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

DouglasPontes/
2020-Q2-full_tweets