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---
license: apache-2.0
base_model: GanjinZero/biobart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-BioBART-50-epochs-1024-input-128-output
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. -->
# fine-tuned-BioBART-50-epochs-1024-input-128-output
This model is a fine-tuned version of [GanjinZero/biobart-base](https://huggingface.co/GanjinZero/biobart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9109
- Rouge1: 0.1191
- Rouge2: 0.0252
- Rougel: 0.105
- Rougelsum: 0.1059
- Gen Len: 16.2
## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 151 | 8.7986 | 0.0 | 0.0 | 0.0 | 0.0 | 14.54 |
| No log | 2.0 | 302 | 4.6009 | 0.007 | 0.0022 | 0.0066 | 0.0067 | 4.73 |
| No log | 3.0 | 453 | 1.9851 | 0.1025 | 0.0246 | 0.091 | 0.0906 | 13.95 |
| 6.1578 | 4.0 | 604 | 1.7001 | 0.0763 | 0.0172 | 0.0666 | 0.0674 | 10.25 |
| 6.1578 | 5.0 | 755 | 1.6023 | 0.1303 | 0.0277 | 0.1167 | 0.1164 | 15.08 |
| 6.1578 | 6.0 | 906 | 1.5322 | 0.0795 | 0.0176 | 0.0732 | 0.0736 | 14.54 |
| 1.4113 | 7.0 | 1057 | 1.4998 | 0.0972 | 0.0241 | 0.0839 | 0.0838 | 13.47 |
| 1.4113 | 8.0 | 1208 | 1.4808 | 0.0992 | 0.0238 | 0.0894 | 0.0898 | 14.28 |
| 1.4113 | 9.0 | 1359 | 1.4964 | 0.1249 | 0.0214 | 0.111 | 0.1106 | 12.36 |
| 0.8834 | 10.0 | 1510 | 1.4858 | 0.1459 | 0.0363 | 0.1235 | 0.1237 | 15.63 |
| 0.8834 | 11.0 | 1661 | 1.4990 | 0.1578 | 0.0403 | 0.1379 | 0.139 | 15.92 |
| 0.8834 | 12.0 | 1812 | 1.5210 | 0.1327 | 0.0253 | 0.1212 | 0.1209 | 15.11 |
| 0.8834 | 13.0 | 1963 | 1.5381 | 0.1372 | 0.038 | 0.1255 | 0.1251 | 15.45 |
| 0.5229 | 14.0 | 2114 | 1.5559 | 0.1383 | 0.0348 | 0.1263 | 0.1263 | 16.49 |
| 0.5229 | 15.0 | 2265 | 1.5824 | 0.1509 | 0.0369 | 0.1336 | 0.1325 | 15.78 |
| 0.5229 | 16.0 | 2416 | 1.6369 | 0.128 | 0.0298 | 0.1176 | 0.1185 | 14.12 |
| 0.2708 | 17.0 | 2567 | 1.6393 | 0.1362 | 0.0429 | 0.1229 | 0.1229 | 15.77 |
| 0.2708 | 18.0 | 2718 | 1.6599 | 0.1521 | 0.0402 | 0.1329 | 0.1333 | 15.34 |
| 0.2708 | 19.0 | 2869 | 1.6705 | 0.1293 | 0.0265 | 0.1165 | 0.1166 | 16.51 |
| 0.1203 | 20.0 | 3020 | 1.6943 | 0.141 | 0.0289 | 0.1273 | 0.1275 | 15.69 |
| 0.1203 | 21.0 | 3171 | 1.6969 | 0.1253 | 0.0337 | 0.1081 | 0.1085 | 16.35 |
| 0.1203 | 22.0 | 3322 | 1.7431 | 0.1319 | 0.0272 | 0.1185 | 0.1185 | 15.63 |
| 0.1203 | 23.0 | 3473 | 1.7434 | 0.1357 | 0.0343 | 0.1253 | 0.125 | 16.39 |
| 0.0509 | 24.0 | 3624 | 1.7507 | 0.1375 | 0.0325 | 0.1233 | 0.1231 | 16.79 |
| 0.0509 | 25.0 | 3775 | 1.7776 | 0.1222 | 0.0328 | 0.1121 | 0.1121 | 16.18 |
| 0.0509 | 26.0 | 3926 | 1.7733 | 0.1265 | 0.0216 | 0.1166 | 0.117 | 16.25 |
| 0.0257 | 27.0 | 4077 | 1.8001 | 0.1238 | 0.0239 | 0.1116 | 0.1113 | 16.44 |
| 0.0257 | 28.0 | 4228 | 1.7955 | 0.1173 | 0.0221 | 0.103 | 0.1046 | 16.64 |
| 0.0257 | 29.0 | 4379 | 1.8143 | 0.1311 | 0.0273 | 0.1186 | 0.1183 | 16.78 |
| 0.0164 | 30.0 | 4530 | 1.8108 | 0.1331 | 0.0296 | 0.1219 | 0.1226 | 15.64 |
| 0.0164 | 31.0 | 4681 | 1.8184 | 0.1245 | 0.0339 | 0.1134 | 0.1143 | 16.55 |
| 0.0164 | 32.0 | 4832 | 1.8545 | 0.1101 | 0.0217 | 0.0982 | 0.0998 | 16.09 |
| 0.0164 | 33.0 | 4983 | 1.8550 | 0.1421 | 0.0322 | 0.1292 | 0.1296 | 16.07 |
| 0.0117 | 34.0 | 5134 | 1.8573 | 0.1309 | 0.0292 | 0.1192 | 0.1193 | 16.0 |
| 0.0117 | 35.0 | 5285 | 1.8453 | 0.1254 | 0.0238 | 0.1133 | 0.1139 | 16.55 |
| 0.0117 | 36.0 | 5436 | 1.8724 | 0.1167 | 0.0241 | 0.1024 | 0.1035 | 15.89 |
| 0.0089 | 37.0 | 5587 | 1.8761 | 0.1345 | 0.0275 | 0.1206 | 0.1208 | 15.87 |
| 0.0089 | 38.0 | 5738 | 1.8772 | 0.1338 | 0.0301 | 0.1216 | 0.1228 | 16.78 |
| 0.0089 | 39.0 | 5889 | 1.8654 | 0.134 | 0.0264 | 0.1193 | 0.1196 | 16.85 |
| 0.0071 | 40.0 | 6040 | 1.8812 | 0.129 | 0.0287 | 0.1181 | 0.1177 | 16.12 |
| 0.0071 | 41.0 | 6191 | 1.8838 | 0.1238 | 0.0274 | 0.1134 | 0.1134 | 16.29 |
| 0.0071 | 42.0 | 6342 | 1.8752 | 0.1334 | 0.0262 | 0.1209 | 0.1214 | 16.66 |
| 0.0071 | 43.0 | 6493 | 1.8993 | 0.1238 | 0.0254 | 0.1111 | 0.1113 | 16.31 |
| 0.0056 | 44.0 | 6644 | 1.8963 | 0.1279 | 0.0346 | 0.1133 | 0.1154 | 16.07 |
| 0.0056 | 45.0 | 6795 | 1.9079 | 0.1225 | 0.0261 | 0.108 | 0.1084 | 16.09 |
| 0.0056 | 46.0 | 6946 | 1.9132 | 0.129 | 0.025 | 0.1157 | 0.1154 | 16.26 |
| 0.0045 | 47.0 | 7097 | 1.9120 | 0.1419 | 0.0362 | 0.1275 | 0.1278 | 15.78 |
| 0.0045 | 48.0 | 7248 | 1.9069 | 0.1316 | 0.0253 | 0.1161 | 0.1165 | 16.38 |
| 0.0045 | 49.0 | 7399 | 1.9099 | 0.1206 | 0.0259 | 0.1074 | 0.1077 | 16.32 |
| 0.0041 | 50.0 | 7550 | 1.9109 | 0.1191 | 0.0252 | 0.105 | 0.1059 | 16.2 |
### Framework versions
- Transformers 4.36.2
- Pytorch 1.12.1+cu113
- Datasets 2.16.1
- Tokenizers 0.15.0
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