transformers tensorboard safetensors bart text2text-generation generated_from_trainer base_model:GanjinZero/biobart-base license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
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-160-output
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# fine-tuned-BioBART-50-epochs-1024-input-160-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: 1.6492
- Rouge1: 0.173
- Rouge2: 0.0346
- Rougel: 0.1373
- Rougelsum: 0.1364
- Gen Len: 40.05

## 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  | 8.7694          | 0.0    | 0.0    | 0.0    | 0.0       | 14.0    |
| No log        | 2.0   | 302  | 4.3319          | 0.0047 | 0.0003 | 0.0047 | 0.0047    | 4.35    |
| No log        | 3.0   | 453  | 1.6898          | 0.1088 | 0.0334 | 0.099  | 0.0996    | 15.96   |
| 6.0134        | 4.0   | 604  | 1.4547          | 0.1004 | 0.0207 | 0.0776 | 0.0769    | 24.61   |
| 6.0134        | 5.0   | 755  | 1.3712          | 0.1532 | 0.0285 | 0.1197 | 0.1194    | 38.39   |
| 6.0134        | 6.0   | 906  | 1.3235          | 0.1144 | 0.0282 | 0.0901 | 0.0913    | 23.41   |
| 1.2432        | 7.0   | 1057 | 1.2835          | 0.1011 | 0.025  | 0.0784 | 0.0798    | 25.49   |
| 1.2432        | 8.0   | 1208 | 1.2733          | 0.1536 | 0.0387 | 0.1169 | 0.1183    | 38.0    |
| 1.2432        | 9.0   | 1359 | 1.2842          | 0.1386 | 0.0244 | 0.1162 | 0.1162    | 20.83   |
| 0.7926        | 10.0  | 1510 | 1.2752          | 0.1812 | 0.0353 | 0.1352 | 0.1363    | 45.95   |
| 0.7926        | 11.0  | 1661 | 1.2846          | 0.1804 | 0.0378 | 0.1452 | 0.1464    | 31.63   |
| 0.7926        | 12.0  | 1812 | 1.2998          | 0.1899 | 0.0432 | 0.1346 | 0.1348    | 48.98   |
| 0.7926        | 13.0  | 1963 | 1.3226          | 0.1809 | 0.0474 | 0.143  | 0.1438    | 33.78   |
| 0.4817        | 14.0  | 2114 | 1.3471          | 0.1425 | 0.0341 | 0.1024 | 0.1028    | 37.38   |
| 0.4817        | 15.0  | 2265 | 1.3651          | 0.1805 | 0.0315 | 0.1402 | 0.1412    | 33.77   |
| 0.4817        | 16.0  | 2416 | 1.3818          | 0.1469 | 0.0333 | 0.1188 | 0.1191    | 30.55   |
| 0.2578        | 17.0  | 2567 | 1.3936          | 0.1734 | 0.0353 | 0.1339 | 0.133     | 36.63   |
| 0.2578        | 18.0  | 2718 | 1.4192          | 0.1988 | 0.0471 | 0.1576 | 0.1587    | 40.01   |
| 0.2578        | 19.0  | 2869 | 1.4183          | 0.1852 | 0.0378 | 0.1449 | 0.1444    | 39.72   |
| 0.1232        | 20.0  | 3020 | 1.4483          | 0.1625 | 0.0442 | 0.1285 | 0.1296    | 36.7    |
| 0.1232        | 21.0  | 3171 | 1.4582          | 0.1771 | 0.0408 | 0.1321 | 0.1329    | 41.33   |
| 0.1232        | 22.0  | 3322 | 1.4860          | 0.1813 | 0.0429 | 0.1458 | 0.1458    | 40.09   |
| 0.1232        | 23.0  | 3473 | 1.5091          | 0.1616 | 0.0373 | 0.1273 | 0.1269    | 37.73   |
| 0.0543        | 24.0  | 3624 | 1.4922          | 0.1914 | 0.0371 | 0.1429 | 0.143     | 45.71   |
| 0.0543        | 25.0  | 3775 | 1.5290          | 0.1642 | 0.0388 | 0.1307 | 0.1315    | 36.5    |
| 0.0543        | 26.0  | 3926 | 1.5310          | 0.1929 | 0.0428 | 0.1524 | 0.1521    | 40.69   |
| 0.0278        | 27.0  | 4077 | 1.5282          | 0.1691 | 0.0414 | 0.1355 | 0.1362    | 39.25   |
| 0.0278        | 28.0  | 4228 | 1.5424          | 0.1749 | 0.0424 | 0.1404 | 0.1408    | 44.13   |
| 0.0278        | 29.0  | 4379 | 1.5573          | 0.1922 | 0.0364 | 0.1549 | 0.1548    | 41.01   |
| 0.0174        | 30.0  | 4530 | 1.5614          | 0.1635 | 0.0358 | 0.1313 | 0.1318    | 39.58   |
| 0.0174        | 31.0  | 4681 | 1.5683          | 0.187  | 0.0427 | 0.1508 | 0.1508    | 39.52   |
| 0.0174        | 32.0  | 4832 | 1.5910          | 0.172  | 0.0262 | 0.1312 | 0.13      | 39.9    |
| 0.0174        | 33.0  | 4983 | 1.5748          | 0.1828 | 0.0429 | 0.1471 | 0.1483    | 38.88   |
| 0.0118        | 34.0  | 5134 | 1.5834          | 0.1702 | 0.034  | 0.1327 | 0.1321    | 38.71   |
| 0.0118        | 35.0  | 5285 | 1.5935          | 0.1987 | 0.0451 | 0.1576 | 0.1577    | 40.79   |
| 0.0118        | 36.0  | 5436 | 1.5993          | 0.193  | 0.0407 | 0.156  | 0.1555    | 41.14   |
| 0.009         | 37.0  | 5587 | 1.6120          | 0.1818 | 0.0393 | 0.1406 | 0.1408    | 40.82   |
| 0.009         | 38.0  | 5738 | 1.6203          | 0.1699 | 0.034  | 0.1344 | 0.1353    | 40.08   |
| 0.009         | 39.0  | 5889 | 1.6201          | 0.1866 | 0.0419 | 0.1446 | 0.1443    | 40.17   |
| 0.0068        | 40.0  | 6040 | 1.6161          | 0.1708 | 0.0279 | 0.136  | 0.1365    | 42.42   |
| 0.0068        | 41.0  | 6191 | 1.6334          | 0.1753 | 0.0396 | 0.14   | 0.14      | 38.92   |
| 0.0068        | 42.0  | 6342 | 1.6321          | 0.1806 | 0.0397 | 0.1448 | 0.1449    | 37.77   |
| 0.0068        | 43.0  | 6493 | 1.6399          | 0.1881 | 0.0373 | 0.1508 | 0.1499    | 40.48   |
| 0.0055        | 44.0  | 6644 | 1.6371          | 0.1847 | 0.0364 | 0.1486 | 0.1479    | 39.22   |
| 0.0055        | 45.0  | 6795 | 1.6421          | 0.1879 | 0.0368 | 0.1499 | 0.1491    | 40.72   |
| 0.0055        | 46.0  | 6946 | 1.6471          | 0.1862 | 0.0381 | 0.1484 | 0.1483    | 40.26   |
| 0.0044        | 47.0  | 7097 | 1.6503          | 0.1719 | 0.036  | 0.1362 | 0.1351    | 40.92   |
| 0.0044        | 48.0  | 7248 | 1.6493          | 0.1711 | 0.036  | 0.1375 | 0.1377    | 39.36   |
| 0.0044        | 49.0  | 7399 | 1.6492          | 0.1738 | 0.0353 | 0.1375 | 0.1365    | 40.71   |
| 0.004         | 50.0  | 7550 | 1.6492          | 0.173  | 0.0346 | 0.1373 | 0.1364    | 40.05   |


### Framework versions

- Transformers 4.36.2
- Pytorch 1.12.1+cu113
- Datasets 2.16.1
- Tokenizers 0.15.0
