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---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_awesome_billsum_model
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. -->
# my_awesome_billsum_model
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4894
- Rouge1: 0.1516
- Rouge2: 0.0523
- Rougel: 0.1224
- Rougelsum: 0.1222
- Gen Len: 20.0
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 4.8246 | 0.0323 | 2 | 4.6334 | 0.1449 | 0.0502 | 0.1214 | 0.1213 | 20.0 |
| 4.906 | 0.0645 | 4 | 4.5100 | 0.1443 | 0.0496 | 0.1209 | 0.1211 | 20.0 |
| 4.8877 | 0.0968 | 6 | 4.3949 | 0.1446 | 0.0488 | 0.121 | 0.1212 | 20.0 |
| 4.7623 | 0.1290 | 8 | 4.1999 | 0.1437 | 0.0487 | 0.1204 | 0.1205 | 20.0 |
| 4.5735 | 0.1613 | 10 | 4.0610 | 0.1446 | 0.0483 | 0.1201 | 0.1203 | 20.0 |
| 4.1697 | 0.1935 | 12 | 3.9348 | 0.1446 | 0.0488 | 0.1202 | 0.1203 | 20.0 |
| 3.9466 | 0.2258 | 14 | 3.7285 | 0.1449 | 0.048 | 0.12 | 0.12 | 20.0 |
| 4.19 | 0.2581 | 16 | 3.6092 | 0.1429 | 0.0465 | 0.1186 | 0.1188 | 20.0 |
| 3.7991 | 0.2903 | 18 | 3.5140 | 0.1411 | 0.0448 | 0.1172 | 0.1172 | 20.0 |
| 3.6421 | 0.3226 | 20 | 3.4145 | 0.1403 | 0.044 | 0.1167 | 0.1167 | 20.0 |
| 3.6484 | 0.3548 | 22 | 3.3426 | 0.1412 | 0.0448 | 0.1171 | 0.1171 | 20.0 |
| 3.7566 | 0.3871 | 24 | 3.2824 | 0.1404 | 0.0441 | 0.1165 | 0.1164 | 20.0 |
| 3.828 | 0.4194 | 26 | 3.2191 | 0.1395 | 0.0431 | 0.1156 | 0.1156 | 20.0 |
| 3.505 | 0.4516 | 28 | 3.1688 | 0.1392 | 0.0428 | 0.1157 | 0.1156 | 20.0 |
| 3.467 | 0.4839 | 30 | 3.1304 | 0.1382 | 0.0419 | 0.1149 | 0.1148 | 20.0 |
| 3.2724 | 0.5161 | 32 | 3.0968 | 0.1383 | 0.0418 | 0.1149 | 0.1148 | 20.0 |
| 3.1572 | 0.5484 | 34 | 3.0638 | 0.1376 | 0.0415 | 0.1142 | 0.114 | 20.0 |
| 3.3082 | 0.5806 | 36 | 3.0362 | 0.1377 | 0.0419 | 0.114 | 0.1138 | 20.0 |
| 3.2159 | 0.6129 | 38 | 3.0100 | 0.1356 | 0.0408 | 0.1127 | 0.1125 | 20.0 |
| 3.3438 | 0.6452 | 40 | 2.9825 | 0.1347 | 0.04 | 0.1116 | 0.1113 | 20.0 |
| 3.2587 | 0.6774 | 42 | 2.9580 | 0.1342 | 0.0406 | 0.1111 | 0.111 | 20.0 |
| 3.0484 | 0.7097 | 44 | 2.9355 | 0.133 | 0.0403 | 0.1112 | 0.1111 | 20.0 |
| 3.1701 | 0.7419 | 46 | 2.9146 | 0.1339 | 0.0404 | 0.1111 | 0.1109 | 20.0 |
| 3.1144 | 0.7742 | 48 | 2.8945 | 0.1324 | 0.0387 | 0.1099 | 0.1097 | 20.0 |
| 3.2611 | 0.8065 | 50 | 2.8756 | 0.1334 | 0.0397 | 0.1105 | 0.1105 | 20.0 |
| 3.0423 | 0.8387 | 52 | 2.8575 | 0.1335 | 0.04 | 0.1109 | 0.1108 | 20.0 |
| 3.1193 | 0.8710 | 54 | 2.8405 | 0.1331 | 0.0391 | 0.1112 | 0.111 | 20.0 |
| 2.9974 | 0.9032 | 56 | 2.8248 | 0.1337 | 0.0393 | 0.1113 | 0.1111 | 20.0 |
| 3.0579 | 0.9355 | 58 | 2.8102 | 0.1337 | 0.0395 | 0.1114 | 0.1113 | 20.0 |
| 3.2434 | 0.9677 | 60 | 2.7964 | 0.1317 | 0.0387 | 0.1101 | 0.11 | 20.0 |
| 2.9767 | 1.0 | 62 | 2.7832 | 0.1307 | 0.0381 | 0.1092 | 0.1091 | 20.0 |
| 2.9854 | 1.0323 | 64 | 2.7704 | 0.1298 | 0.0376 | 0.1081 | 0.1081 | 20.0 |
| 2.8919 | 1.0645 | 66 | 2.7586 | 0.1304 | 0.0375 | 0.1082 | 0.1082 | 20.0 |
| 2.9225 | 1.0968 | 68 | 2.7472 | 0.1316 | 0.0388 | 0.1093 | 0.1092 | 20.0 |
| 3.173 | 1.1290 | 70 | 2.7363 | 0.1309 | 0.039 | 0.1087 | 0.1086 | 20.0 |
| 3.0448 | 1.1613 | 72 | 2.7258 | 0.1311 | 0.0388 | 0.1085 | 0.1084 | 20.0 |
| 3.0989 | 1.1935 | 74 | 2.7156 | 0.132 | 0.0398 | 0.1094 | 0.1094 | 20.0 |
| 3.0072 | 1.2258 | 76 | 2.7057 | 0.1327 | 0.0404 | 0.11 | 0.11 | 20.0 |
| 2.7462 | 1.2581 | 78 | 2.6968 | 0.1328 | 0.0403 | 0.1098 | 0.1098 | 20.0 |
| 3.0383 | 1.2903 | 80 | 2.6879 | 0.1336 | 0.0401 | 0.1095 | 0.1095 | 20.0 |
| 3.1326 | 1.3226 | 82 | 2.6793 | 0.1348 | 0.0413 | 0.111 | 0.1108 | 20.0 |
| 2.9859 | 1.3548 | 84 | 2.6710 | 0.1336 | 0.0413 | 0.1102 | 0.1102 | 20.0 |
| 2.8721 | 1.3871 | 86 | 2.6630 | 0.1332 | 0.0414 | 0.1097 | 0.1097 | 20.0 |
| 2.996 | 1.4194 | 88 | 2.6555 | 0.1346 | 0.0419 | 0.1103 | 0.1102 | 20.0 |
| 2.9725 | 1.4516 | 90 | 2.6484 | 0.1348 | 0.0415 | 0.1108 | 0.1106 | 20.0 |
| 3.0609 | 1.4839 | 92 | 2.6416 | 0.1342 | 0.0415 | 0.1102 | 0.1102 | 20.0 |
| 2.7738 | 1.5161 | 94 | 2.6351 | 0.1356 | 0.042 | 0.1112 | 0.1111 | 20.0 |
| 2.9562 | 1.5484 | 96 | 2.6290 | 0.1368 | 0.0431 | 0.1122 | 0.112 | 20.0 |
| 2.6523 | 1.5806 | 98 | 2.6231 | 0.1372 | 0.0432 | 0.1126 | 0.1125 | 20.0 |
| 3.0343 | 1.6129 | 100 | 2.6174 | 0.1371 | 0.0427 | 0.1124 | 0.1123 | 20.0 |
| 2.7485 | 1.6452 | 102 | 2.6121 | 0.138 | 0.0434 | 0.1128 | 0.1127 | 20.0 |
| 2.9437 | 1.6774 | 104 | 2.6069 | 0.1379 | 0.0434 | 0.1132 | 0.113 | 20.0 |
| 2.8865 | 1.7097 | 106 | 2.6018 | 0.1377 | 0.0432 | 0.1129 | 0.1127 | 20.0 |
| 2.9826 | 1.7419 | 108 | 2.5967 | 0.1386 | 0.0435 | 0.1138 | 0.1136 | 20.0 |
| 2.8272 | 1.7742 | 110 | 2.5918 | 0.1382 | 0.0435 | 0.1137 | 0.1135 | 20.0 |
| 2.7165 | 1.8065 | 112 | 2.5874 | 0.1379 | 0.0435 | 0.1135 | 0.1133 | 20.0 |
| 2.9133 | 1.8387 | 114 | 2.5833 | 0.1377 | 0.0427 | 0.1129 | 0.1127 | 20.0 |
| 2.8366 | 1.8710 | 116 | 2.5795 | 0.1382 | 0.0437 | 0.1137 | 0.1135 | 20.0 |
| 2.8033 | 1.9032 | 118 | 2.5760 | 0.1382 | 0.0443 | 0.1139 | 0.1137 | 20.0 |
| 2.8846 | 1.9355 | 120 | 2.5723 | 0.1378 | 0.0437 | 0.1132 | 0.1131 | 20.0 |
| 3.0411 | 1.9677 | 122 | 2.5688 | 0.1379 | 0.0438 | 0.1134 | 0.1133 | 20.0 |
| 2.931 | 2.0 | 124 | 2.5654 | 0.1387 | 0.0439 | 0.114 | 0.1139 | 20.0 |
| 2.7692 | 2.0323 | 126 | 2.5619 | 0.1392 | 0.0436 | 0.1141 | 0.1141 | 20.0 |
| 2.576 | 2.0645 | 128 | 2.5588 | 0.1405 | 0.0438 | 0.1144 | 0.1144 | 20.0 |
| 2.9965 | 2.0968 | 130 | 2.5559 | 0.1414 | 0.0442 | 0.1151 | 0.1149 | 20.0 |
| 2.7233 | 2.1290 | 132 | 2.5532 | 0.1418 | 0.0439 | 0.1151 | 0.1151 | 20.0 |
| 2.7718 | 2.1613 | 134 | 2.5507 | 0.143 | 0.0446 | 0.1158 | 0.1157 | 20.0 |
| 2.7089 | 2.1935 | 136 | 2.5482 | 0.1435 | 0.0455 | 0.1162 | 0.1161 | 20.0 |
| 2.9317 | 2.2258 | 138 | 2.5457 | 0.1433 | 0.0457 | 0.1158 | 0.1158 | 20.0 |
| 2.8748 | 2.2581 | 140 | 2.5432 | 0.1435 | 0.046 | 0.1162 | 0.1162 | 20.0 |
| 2.9315 | 2.2903 | 142 | 2.5407 | 0.1446 | 0.0466 | 0.117 | 0.1169 | 20.0 |
| 2.7498 | 2.3226 | 144 | 2.5383 | 0.1452 | 0.0474 | 0.1177 | 0.1176 | 20.0 |
| 2.9018 | 2.3548 | 146 | 2.5358 | 0.1452 | 0.0474 | 0.1175 | 0.1175 | 20.0 |
| 2.8626 | 2.3871 | 148 | 2.5332 | 0.1453 | 0.0475 | 0.1174 | 0.1173 | 20.0 |
| 2.8584 | 2.4194 | 150 | 2.5309 | 0.1451 | 0.0476 | 0.1175 | 0.1174 | 20.0 |
| 2.8144 | 2.4516 | 152 | 2.5288 | 0.1459 | 0.0482 | 0.1177 | 0.1177 | 20.0 |
| 2.9953 | 2.4839 | 154 | 2.5268 | 0.1462 | 0.0486 | 0.118 | 0.1179 | 20.0 |
| 2.8001 | 2.5161 | 156 | 2.5249 | 0.1463 | 0.0488 | 0.118 | 0.1179 | 20.0 |
| 2.9155 | 2.5484 | 158 | 2.5232 | 0.1458 | 0.0487 | 0.1178 | 0.1177 | 20.0 |
| 2.8051 | 2.5806 | 160 | 2.5215 | 0.1464 | 0.0492 | 0.1185 | 0.1184 | 20.0 |
| 2.5662 | 2.6129 | 162 | 2.5199 | 0.147 | 0.0497 | 0.1189 | 0.1187 | 20.0 |
| 2.6469 | 2.6452 | 164 | 2.5184 | 0.1469 | 0.0493 | 0.1188 | 0.1186 | 20.0 |
| 2.8197 | 2.6774 | 166 | 2.5169 | 0.1479 | 0.0499 | 0.1199 | 0.1197 | 20.0 |
| 2.5777 | 2.7097 | 168 | 2.5155 | 0.1484 | 0.0502 | 0.1202 | 0.1201 | 20.0 |
| 2.8761 | 2.7419 | 170 | 2.5141 | 0.1479 | 0.0497 | 0.1199 | 0.1197 | 20.0 |
| 2.5811 | 2.7742 | 172 | 2.5128 | 0.148 | 0.0499 | 0.1202 | 0.1199 | 20.0 |
| 2.7054 | 2.8065 | 174 | 2.5116 | 0.1478 | 0.0497 | 0.1199 | 0.1197 | 20.0 |
| 3.0032 | 2.8387 | 176 | 2.5105 | 0.1476 | 0.0494 | 0.1195 | 0.1194 | 20.0 |
| 2.7478 | 2.8710 | 178 | 2.5093 | 0.1476 | 0.0494 | 0.1195 | 0.1194 | 20.0 |
| 2.9108 | 2.9032 | 180 | 2.5083 | 0.1478 | 0.0496 | 0.1194 | 0.1193 | 20.0 |
| 2.6513 | 2.9355 | 182 | 2.5072 | 0.1478 | 0.0499 | 0.1197 | 0.1195 | 20.0 |
| 2.8323 | 2.9677 | 184 | 2.5061 | 0.1475 | 0.0495 | 0.1194 | 0.1192 | 20.0 |
| 2.8963 | 3.0 | 186 | 2.5051 | 0.1483 | 0.0501 | 0.12 | 0.1197 | 20.0 |
| 2.815 | 3.0323 | 188 | 2.5041 | 0.1486 | 0.0503 | 0.1201 | 0.1198 | 20.0 |
| 2.9109 | 3.0645 | 190 | 2.5030 | 0.1487 | 0.0503 | 0.1203 | 0.12 | 20.0 |
| 2.6712 | 3.0968 | 192 | 2.5021 | 0.1498 | 0.0505 | 0.1209 | 0.1207 | 20.0 |
| 2.6606 | 3.1290 | 194 | 2.5011 | 0.1498 | 0.0505 | 0.1209 | 0.1207 | 20.0 |
| 2.7432 | 3.1613 | 196 | 2.5002 | 0.1498 | 0.0505 | 0.1209 | 0.1207 | 20.0 |
| 2.9712 | 3.1935 | 198 | 2.4992 | 0.1498 | 0.0505 | 0.1209 | 0.1207 | 20.0 |
| 2.6893 | 3.2258 | 200 | 2.4985 | 0.1497 | 0.0503 | 0.1206 | 0.1204 | 20.0 |
| 2.8161 | 3.2581 | 202 | 2.4977 | 0.1492 | 0.0498 | 0.1203 | 0.1202 | 20.0 |
| 3.1472 | 3.2903 | 204 | 2.4969 | 0.1492 | 0.0498 | 0.1203 | 0.1202 | 20.0 |
| 2.5583 | 3.3226 | 206 | 2.4963 | 0.1492 | 0.0499 | 0.1203 | 0.1201 | 20.0 |
| 2.7874 | 3.3548 | 208 | 2.4956 | 0.1499 | 0.0502 | 0.121 | 0.1208 | 20.0 |
| 2.6359 | 3.3871 | 210 | 2.4950 | 0.1502 | 0.0505 | 0.1212 | 0.121 | 20.0 |
| 2.8058 | 3.4194 | 212 | 2.4945 | 0.1499 | 0.0505 | 0.1209 | 0.1207 | 20.0 |
| 2.6235 | 3.4516 | 214 | 2.4939 | 0.1502 | 0.0506 | 0.1212 | 0.121 | 20.0 |
| 2.6428 | 3.4839 | 216 | 2.4934 | 0.1506 | 0.0513 | 0.1216 | 0.1215 | 20.0 |
| 2.6676 | 3.5161 | 218 | 2.4929 | 0.1508 | 0.0516 | 0.1218 | 0.1216 | 20.0 |
| 2.5883 | 3.5484 | 220 | 2.4925 | 0.151 | 0.052 | 0.1219 | 0.1218 | 20.0 |
| 2.9245 | 3.5806 | 222 | 2.4921 | 0.151 | 0.052 | 0.122 | 0.1219 | 20.0 |
| 2.9351 | 3.6129 | 224 | 2.4917 | 0.151 | 0.052 | 0.122 | 0.1219 | 20.0 |
| 2.9175 | 3.6452 | 226 | 2.4913 | 0.151 | 0.0519 | 0.1218 | 0.1218 | 20.0 |
| 2.6997 | 3.6774 | 228 | 2.4910 | 0.1509 | 0.0516 | 0.1218 | 0.1217 | 20.0 |
| 2.7747 | 3.7097 | 230 | 2.4907 | 0.1508 | 0.0515 | 0.1217 | 0.1216 | 20.0 |
| 2.5892 | 3.7419 | 232 | 2.4904 | 0.1508 | 0.0515 | 0.1217 | 0.1216 | 20.0 |
| 2.7554 | 3.7742 | 234 | 2.4902 | 0.1506 | 0.0515 | 0.1216 | 0.1215 | 20.0 |
| 2.8548 | 3.8065 | 236 | 2.4900 | 0.1516 | 0.0523 | 0.1224 | 0.1222 | 20.0 |
| 2.7879 | 3.8387 | 238 | 2.4898 | 0.1516 | 0.0523 | 0.1224 | 0.1222 | 20.0 |
| 2.7142 | 3.8710 | 240 | 2.4896 | 0.1514 | 0.0521 | 0.1223 | 0.1222 | 20.0 |
| 2.7282 | 3.9032 | 242 | 2.4895 | 0.1513 | 0.0521 | 0.1222 | 0.1221 | 20.0 |
| 2.6589 | 3.9355 | 244 | 2.4894 | 0.1511 | 0.0519 | 0.1222 | 0.1221 | 20.0 |
| 2.7158 | 3.9677 | 246 | 2.4894 | 0.1514 | 0.0523 | 0.1223 | 0.1221 | 20.0 |
| 2.7397 | 4.0 | 248 | 2.4894 | 0.1516 | 0.0523 | 0.1224 | 0.1222 | 20.0 |
### Framework versions
- Transformers 4.55.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4
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