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---
license: mit
base_model: cardiffnlp/twitter-roberta-base-2019-90m
tags:
- generated_from_trainer
model-index:
- name: 2020-Q1-90p-filtered_2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 2020-Q1-90p-filtered_2
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: 1.9012
## 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 | 0.16 | 8000 | 2.2376 |
| 2.4394 | 0.33 | 16000 | 2.1557 |
| 2.4394 | 0.49 | 24000 | 2.0965 |
| 2.2403 | 0.66 | 32000 | 2.0637 |
| 2.2403 | 0.82 | 40000 | 2.0620 |
| 2.1859 | 0.98 | 48000 | 2.0427 |
| 2.1859 | 1.15 | 56000 | 2.0440 |
| 2.1472 | 1.31 | 64000 | 2.0177 |
| 2.1472 | 1.48 | 72000 | 1.9980 |
| 2.1334 | 1.64 | 80000 | 2.0021 |
| 2.1334 | 1.8 | 88000 | 1.9963 |
| 2.1271 | 1.97 | 96000 | 1.9918 |
| 2.1271 | 2.13 | 104000 | 1.9889 |
| 2.1065 | 2.29 | 112000 | 1.9689 |
| 2.1065 | 2.46 | 120000 | 1.9919 |
| 2.105 | 2.62 | 128000 | 1.9706 |
| 2.105 | 2.79 | 136000 | 1.9725 |
| 2.1033 | 2.95 | 144000 | 2.0009 |
| 2.1033 | 3.11 | 152000 | 1.9661 |
| 2.0934 | 3.28 | 160000 | 1.9641 |
| 2.0934 | 3.44 | 168000 | 1.9733 |
| 2.0899 | 3.61 | 176000 | 1.9747 |
| 2.0899 | 3.77 | 184000 | 1.9442 |
| 2.0903 | 3.93 | 192000 | 1.9586 |
| 2.0903 | 4.1 | 200000 | 1.9586 |
| 2.0842 | 4.26 | 208000 | 1.9402 |
| 2.0842 | 4.43 | 216000 | 1.9483 |
| 2.0761 | 4.59 | 224000 | 1.9532 |
| 2.0761 | 4.75 | 232000 | 1.9456 |
| 2.0799 | 4.92 | 240000 | 1.9322 |
| 2.0799 | 5.08 | 248000 | 1.9460 |
| 2.0704 | 5.24 | 256000 | 1.9478 |
| 2.0704 | 5.41 | 264000 | 1.9435 |
| 2.0727 | 5.57 | 272000 | 1.9356 |
| 2.0727 | 5.74 | 280000 | 1.9543 |
| 2.073 | 5.9 | 288000 | 1.9542 |
| 2.073 | 6.06 | 296000 | 1.9503 |
| 2.0647 | 6.23 | 304000 | 1.9437 |
| 2.0647 | 6.39 | 312000 | 1.9450 |
| 2.0668 | 6.56 | 320000 | 1.9221 |
| 2.0668 | 6.72 | 328000 | 1.9277 |
| 2.0695 | 6.88 | 336000 | 1.9357 |
| 2.0695 | 7.05 | 344000 | 1.9244 |
| 2.0652 | 7.21 | 352000 | 1.9387 |
| 2.0652 | 7.38 | 360000 | 1.9355 |
| 2.0607 | 7.54 | 368000 | 1.9390 |
| 2.0607 | 7.7 | 376000 | 1.9359 |
| 2.0707 | 7.87 | 384000 | 1.9393 |
| 2.0707 | 8.03 | 392000 | 1.9217 |
| 2.0621 | 8.2 | 400000 | 1.9284 |
| 2.0621 | 8.36 | 408000 | 1.9383 |
| 2.0643 | 8.52 | 416000 | 1.9224 |
| 2.0643 | 8.69 | 424000 | 1.9284 |
| 2.0498 | 8.85 | 432000 | 1.9399 |
| 2.0498 | 9.01 | 440000 | 1.9427 |
| 2.0689 | 9.18 | 448000 | 1.9351 |
| 2.0689 | 9.34 | 456000 | 1.9313 |
| 2.0511 | 9.51 | 464000 | 1.9392 |
| 2.0511 | 9.67 | 472000 | 1.9278 |
| 2.0664 | 9.83 | 480000 | 1.9385 |
| 2.0664 | 10.0 | 488000 | 1.9472 |
| 2.0565 | 10.16 | 496000 | 1.9377 |
| 2.0565 | 10.33 | 504000 | 1.9481 |
| 2.0566 | 10.49 | 512000 | 1.9454 |
| 2.0566 | 10.65 | 520000 | 1.9244 |
| 2.0523 | 10.82 | 528000 | 1.9358 |
| 2.0523 | 10.98 | 536000 | 1.9176 |
| 2.0554 | 11.15 | 544000 | 1.9284 |
| 2.0554 | 11.31 | 552000 | 1.9287 |
| 2.0485 | 11.47 | 560000 | 1.9237 |
| 2.0485 | 11.64 | 568000 | 1.9209 |
| 2.0485 | 11.8 | 576000 | 1.9262 |
| 2.0485 | 11.97 | 584000 | 1.9208 |
| 2.0542 | 12.13 | 592000 | 1.9320 |
| 2.0542 | 12.29 | 600000 | 1.9077 |
| 2.0527 | 12.46 | 608000 | 1.9249 |
| 2.0527 | 12.62 | 616000 | 1.9192 |
| 2.0606 | 12.78 | 624000 | 1.9152 |
| 2.0606 | 12.95 | 632000 | 1.9194 |
| 2.0542 | 13.11 | 640000 | 1.9198 |
| 2.0542 | 13.28 | 648000 | 1.9135 |
| 2.0593 | 13.44 | 656000 | 1.9192 |
| 2.0593 | 13.6 | 664000 | 1.9257 |
| 2.0467 | 13.77 | 672000 | 1.9135 |
| 2.0467 | 13.93 | 680000 | 1.8995 |
| 2.0535 | 14.1 | 688000 | 1.9306 |
| 2.0535 | 14.26 | 696000 | 1.9278 |
| 2.0559 | 14.42 | 704000 | 1.9137 |
| 2.0559 | 14.59 | 712000 | 1.9165 |
| 2.0544 | 14.75 | 720000 | 1.9219 |
| 2.0544 | 14.92 | 728000 | 1.9200 |
| 2.0493 | 15.08 | 736000 | 1.9242 |
| 2.0493 | 15.24 | 744000 | 1.9264 |
| 2.0538 | 15.41 | 752000 | 1.9333 |
| 2.0538 | 15.57 | 760000 | 1.9126 |
| 2.0457 | 15.73 | 768000 | 1.9023 |
| 2.0457 | 15.9 | 776000 | 1.9154 |
| 2.0436 | 16.06 | 784000 | 1.8947 |
| 2.0436 | 16.23 | 792000 | 1.9198 |
| 2.0527 | 16.39 | 800000 | 1.9125 |
| 2.0527 | 16.55 | 808000 | 1.9129 |
| 2.0484 | 16.72 | 816000 | 1.9302 |
| 2.0484 | 16.88 | 824000 | 1.9152 |
| 2.0535 | 17.05 | 832000 | 1.9223 |
| 2.0535 | 17.21 | 840000 | 1.9195 |
| 2.0516 | 17.37 | 848000 | 1.9072 |
| 2.0516 | 17.54 | 856000 | 1.9210 |
| 2.0546 | 17.7 | 864000 | 1.9014 |
| 2.0546 | 17.87 | 872000 | 1.9130 |
| 2.0439 | 18.03 | 880000 | 1.9064 |
| 2.0439 | 18.19 | 888000 | 1.9166 |
| 2.0391 | 18.36 | 896000 | 1.9310 |
| 2.0391 | 18.52 | 904000 | 1.9064 |
| 2.0568 | 18.69 | 912000 | 1.9107 |
| 2.0568 | 18.85 | 920000 | 1.9317 |
| 2.047 | 19.01 | 928000 | 1.9235 |
| 2.047 | 19.18 | 936000 | 1.9173 |
| 2.0431 | 19.34 | 944000 | 1.8946 |
| 2.0431 | 19.5 | 952000 | 1.9247 |
| 2.0444 | 19.67 | 960000 | 1.9106 |
| 2.0444 | 19.83 | 968000 | 1.9023 |
| 2.0465 | 20.0 | 976000 | 1.9196 |
| 2.0465 | 20.16 | 984000 | 1.9112 |
| 2.0454 | 20.32 | 992000 | 1.9046 |
| 2.0454 | 20.49 | 1000000 | 1.9032 |
| 2.04 | 20.65 | 1008000 | 1.9130 |
| 2.04 | 20.82 | 1016000 | 1.9223 |
| 2.0406 | 20.98 | 1024000 | 1.9261 |
| 2.0406 | 21.14 | 1032000 | 1.9014 |
| 2.0401 | 21.31 | 1040000 | 1.9052 |
| 2.0401 | 21.47 | 1048000 | 1.9005 |
| 2.044 | 21.64 | 1056000 | 1.9044 |
| 2.044 | 21.8 | 1064000 | 1.9170 |
| 2.0401 | 21.96 | 1072000 | 1.9103 |
| 2.0401 | 22.13 | 1080000 | 1.8971 |
| 2.0458 | 22.29 | 1088000 | 1.9257 |
| 2.0458 | 22.45 | 1096000 | 1.9029 |
| 2.0414 | 22.62 | 1104000 | 1.9150 |
| 2.0414 | 22.78 | 1112000 | 1.9124 |
| 2.0419 | 22.95 | 1120000 | 1.9030 |
| 2.0419 | 23.11 | 1128000 | 1.9145 |
| 2.0415 | 23.27 | 1136000 | 1.9132 |
| 2.0415 | 23.44 | 1144000 | 1.9054 |
| 2.0394 | 23.6 | 1152000 | 1.9155 |
| 2.0394 | 23.77 | 1160000 | 1.9147 |
| 2.0414 | 23.93 | 1168000 | 1.9130 |
| 2.0414 | 24.09 | 1176000 | 1.9002 |
| 2.036 | 24.26 | 1184000 | 1.8991 |
| 2.036 | 24.42 | 1192000 | 1.9203 |
| 2.0393 | 24.59 | 1200000 | 1.9327 |
| 2.0393 | 24.75 | 1208000 | 1.9099 |
| 2.0375 | 24.91 | 1216000 | 1.9097 |
| 2.0375 | 25.08 | 1224000 | 1.9006 |
| 2.0384 | 25.24 | 1232000 | 1.9063 |
| 2.0384 | 25.41 | 1240000 | 1.9057 |
| 2.0392 | 25.57 | 1248000 | 1.9037 |
| 2.0392 | 25.73 | 1256000 | 1.9013 |
| 2.0503 | 25.9 | 1264000 | 1.9037 |
| 2.0503 | 26.06 | 1272000 | 1.9042 |
| 2.0418 | 26.22 | 1280000 | 1.8966 |
| 2.0418 | 26.39 | 1288000 | 1.9187 |
| 2.0416 | 26.55 | 1296000 | 1.9098 |
| 2.0416 | 26.72 | 1304000 | 1.9153 |
| 2.0396 | 26.88 | 1312000 | 1.9164 |
| 2.0396 | 27.04 | 1320000 | 1.8867 |
| 2.0397 | 27.21 | 1328000 | 1.8969 |
| 2.0397 | 27.37 | 1336000 | 1.9155 |
| 2.0442 | 27.54 | 1344000 | 1.9004 |
| 2.0442 | 27.7 | 1352000 | 1.9027 |
| 2.0332 | 27.86 | 1360000 | 1.9095 |
| 2.0332 | 28.03 | 1368000 | 1.9134 |
| 2.0398 | 28.19 | 1376000 | 1.9083 |
| 2.0398 | 28.36 | 1384000 | 1.9041 |
| 2.0387 | 28.52 | 1392000 | 1.8980 |
| 2.0387 | 28.68 | 1400000 | 1.9209 |
| 2.0378 | 28.85 | 1408000 | 1.8962 |
| 2.0378 | 29.01 | 1416000 | 1.8981 |
| 2.0359 | 29.17 | 1424000 | 1.9078 |
| 2.0359 | 29.34 | 1432000 | 1.8962 |
| 2.0357 | 29.5 | 1440000 | 1.8843 |
| 2.0357 | 29.67 | 1448000 | 1.9157 |
| 2.0367 | 29.83 | 1456000 | 1.9278 |
| 2.0367 | 29.99 | 1464000 | 1.9009 |
| 2.0442 | 30.16 | 1472000 | 1.8969 |
| 2.0442 | 30.32 | 1480000 | 1.9086 |
| 2.0401 | 30.49 | 1488000 | 1.9059 |
| 2.0401 | 30.65 | 1496000 | 1.8997 |
| 2.0293 | 30.81 | 1504000 | 1.9014 |
| 2.0293 | 30.98 | 1512000 | 1.8971 |
| 2.035 | 31.14 | 1520000 | 1.9114 |
| 2.035 | 31.31 | 1528000 | 1.9108 |
| 2.0389 | 31.47 | 1536000 | 1.8971 |
| 2.0389 | 31.63 | 1544000 | 1.9082 |
| 2.0346 | 31.8 | 1552000 | 1.9209 |
| 2.0346 | 31.96 | 1560000 | 1.9018 |
| 2.0428 | 32.13 | 1568000 | 1.8988 |
| 2.0428 | 32.29 | 1576000 | 1.9089 |
| 2.0286 | 32.45 | 1584000 | 1.8983 |
| 2.0286 | 32.62 | 1592000 | 1.9030 |
| 2.037 | 32.78 | 1600000 | 1.9042 |
| 2.037 | 32.94 | 1608000 | 1.9022 |
| 2.0348 | 33.11 | 1616000 | 1.8988 |
| 2.0348 | 33.27 | 1624000 | 1.9159 |
| 2.042 | 33.44 | 1632000 | 1.8934 |
| 2.042 | 33.6 | 1640000 | 1.8908 |
| 2.0426 | 33.76 | 1648000 | 1.8878 |
| 2.0426 | 33.93 | 1656000 | 1.8882 |
| 2.0293 | 34.09 | 1664000 | 1.9031 |
| 2.0293 | 34.26 | 1672000 | 1.9006 |
| 2.0401 | 34.42 | 1680000 | 1.9066 |
| 2.0401 | 34.58 | 1688000 | 1.8970 |
| 2.0315 | 34.75 | 1696000 | 1.8953 |
| 2.0315 | 34.91 | 1704000 | 1.9030 |
| 2.0393 | 35.08 | 1712000 | 1.9089 |
| 2.0393 | 35.24 | 1720000 | 1.9037 |
| 2.0422 | 35.4 | 1728000 | 1.8991 |
| 2.0422 | 35.57 | 1736000 | 1.8826 |
| 2.0307 | 35.73 | 1744000 | 1.9027 |
| 2.0307 | 35.9 | 1752000 | 1.9173 |
| 2.0414 | 36.06 | 1760000 | 1.9065 |
| 2.0414 | 36.22 | 1768000 | 1.8985 |
| 2.0393 | 36.39 | 1776000 | 1.8849 |
| 2.0393 | 36.55 | 1784000 | 1.8945 |
| 2.0302 | 36.71 | 1792000 | 1.8962 |
| 2.0302 | 36.88 | 1800000 | 1.9015 |
| 2.0344 | 37.04 | 1808000 | 1.8924 |
| 2.0344 | 37.21 | 1816000 | 1.8804 |
| 2.0303 | 37.37 | 1824000 | 1.8947 |
| 2.0303 | 37.53 | 1832000 | 1.8917 |
| 2.0318 | 37.7 | 1840000 | 1.8992 |
| 2.0318 | 37.86 | 1848000 | 1.9018 |
| 2.039 | 38.03 | 1856000 | 1.8903 |
| 2.039 | 38.19 | 1864000 | 1.9089 |
| 2.0319 | 38.35 | 1872000 | 1.9093 |
| 2.0319 | 38.52 | 1880000 | 1.8951 |
| 2.0359 | 38.68 | 1888000 | 1.8970 |
| 2.0359 | 38.85 | 1896000 | 1.8995 |
| 2.0353 | 39.01 | 1904000 | 1.8888 |
| 2.0353 | 39.17 | 1912000 | 1.9149 |
| 2.0343 | 39.34 | 1920000 | 1.8881 |
| 2.0343 | 39.5 | 1928000 | 1.8935 |
| 2.0395 | 39.66 | 1936000 | 1.8938 |
| 2.0395 | 39.83 | 1944000 | 1.8929 |
| 2.0316 | 39.99 | 1952000 | 1.9186 |
| 2.0316 | 40.16 | 1960000 | 1.9189 |
| 2.0302 | 40.32 | 1968000 | 1.9125 |
| 2.0302 | 40.48 | 1976000 | 1.9078 |
| 2.0355 | 40.65 | 1984000 | 1.8975 |
| 2.0355 | 40.81 | 1992000 | 1.8929 |
| 2.0332 | 40.98 | 2000000 | 1.8899 |
| 2.0332 | 41.14 | 2008000 | 1.9043 |
| 2.0327 | 41.3 | 2016000 | 1.9086 |
| 2.0327 | 41.47 | 2024000 | 1.8944 |
| 2.0414 | 41.63 | 2032000 | 1.9029 |
| 2.0414 | 41.8 | 2040000 | 1.8990 |
| 2.0327 | 41.96 | 2048000 | 1.9175 |
| 2.0327 | 42.12 | 2056000 | 1.8888 |
| 2.0428 | 42.29 | 2064000 | 1.8971 |
| 2.0428 | 42.45 | 2072000 | 1.9071 |
| 2.0337 | 42.62 | 2080000 | 1.8968 |
| 2.0337 | 42.78 | 2088000 | 1.9060 |
| 2.0394 | 42.94 | 2096000 | 1.9028 |
| 2.0394 | 43.11 | 2104000 | 1.8917 |
| 2.0314 | 43.27 | 2112000 | 1.8868 |
| 2.0314 | 43.43 | 2120000 | 1.9087 |
| 2.0368 | 43.6 | 2128000 | 1.8951 |
| 2.0368 | 43.76 | 2136000 | 1.8938 |
| 2.0298 | 43.93 | 2144000 | 1.8874 |
| 2.0298 | 44.09 | 2152000 | 1.9065 |
| 2.0353 | 44.25 | 2160000 | 1.9097 |
| 2.0353 | 44.42 | 2168000 | 1.8985 |
| 2.0324 | 44.58 | 2176000 | 1.9160 |
| 2.0324 | 44.75 | 2184000 | 1.9060 |
| 2.0316 | 44.91 | 2192000 | 1.8912 |
| 2.0316 | 45.07 | 2200000 | 1.9014 |
| 2.0322 | 45.24 | 2208000 | 1.9031 |
| 2.0322 | 45.4 | 2216000 | 1.9086 |
| 2.035 | 45.57 | 2224000 | 1.9147 |
| 2.035 | 45.73 | 2232000 | 1.9004 |
| 2.0431 | 45.89 | 2240000 | 1.9027 |
| 2.0431 | 46.06 | 2248000 | 1.8916 |
| 2.0347 | 46.22 | 2256000 | 1.9049 |
| 2.0347 | 46.38 | 2264000 | 1.8973 |
| 2.0353 | 46.55 | 2272000 | 1.8932 |
| 2.0353 | 46.71 | 2280000 | 1.9121 |
| 2.0309 | 46.88 | 2288000 | 1.8973 |
| 2.0309 | 47.04 | 2296000 | 1.8986 |
| 2.0359 | 47.2 | 2304000 | 1.9202 |
| 2.0359 | 47.37 | 2312000 | 1.8778 |
| 2.037 | 47.53 | 2320000 | 1.9137 |
| 2.037 | 47.7 | 2328000 | 1.9095 |
| 2.0306 | 47.86 | 2336000 | 1.9040 |
| 2.0306 | 48.02 | 2344000 | 1.8932 |
| 2.0342 | 48.19 | 2352000 | 1.9152 |
| 2.0342 | 48.35 | 2360000 | 1.9059 |
| 2.0457 | 48.52 | 2368000 | 1.8845 |
| 2.0457 | 48.68 | 2376000 | 1.9040 |
| 2.0349 | 48.84 | 2384000 | 1.9000 |
| 2.0349 | 49.01 | 2392000 | 1.9059 |
| 2.0322 | 49.17 | 2400000 | 1.8926 |
### Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
|