---
license: apache-2.0
base_model: GanjinZero/biobart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-BioBART-20-epochs-1500-input-256-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-20-epochs-1500-input-256-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: 0.9257
- Rouge1: 0.1655
- Rouge2: 0.0291
- Rougel: 0.1256
- Rougelsum: 0.1266
- Gen Len: 34.62

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 151  | 6.1052          | 0.0511 | 0.0    | 0.047  | 0.0474    | 22.48   |
| No log        | 2.0   | 302  | 1.1483          | 0.077  | 0.0156 | 0.0673 | 0.0678    | 11.56   |
| No log        | 3.0   | 453  | 0.9767          | 0.0744 | 0.0182 | 0.0537 | 0.0557    | 23.57   |
| 4.0217        | 4.0   | 604  | 0.9160          | 0.1355 | 0.033  | 0.1053 | 0.1042    | 37.77   |
| 4.0217        | 5.0   | 755  | 0.8850          | 0.1682 | 0.0352 | 0.1342 | 0.1342    | 41.92   |
| 4.0217        | 6.0   | 906  | 0.8736          | 0.1342 | 0.0308 | 0.1037 | 0.1037    | 35.34   |
| 0.761         | 7.0   | 1057 | 0.8582          | 0.144  | 0.0361 | 0.1082 | 0.1095    | 39.27   |
| 0.761         | 8.0   | 1208 | 0.8551          | 0.165  | 0.0392 | 0.1233 | 0.1254    | 39.55   |
| 0.761         | 9.0   | 1359 | 0.8623          | 0.141  | 0.0302 | 0.1169 | 0.1179    | 23.69   |
| 0.5257        | 10.0  | 1510 | 0.8642          | 0.1715 | 0.0436 | 0.1249 | 0.1267    | 45.78   |
| 0.5257        | 11.0  | 1661 | 0.8705          | 0.1702 | 0.0331 | 0.1386 | 0.1385    | 30.28   |
| 0.5257        | 12.0  | 1812 | 0.8761          | 0.169  | 0.035  | 0.1247 | 0.1254    | 42.74   |
| 0.5257        | 13.0  | 1963 | 0.8938          | 0.1719 | 0.0376 | 0.139  | 0.1389    | 29.73   |
| 0.368         | 14.0  | 2114 | 0.8907          | 0.1716 | 0.0402 | 0.1371 | 0.1377    | 36.07   |
| 0.368         | 15.0  | 2265 | 0.9027          | 0.1677 | 0.0324 | 0.1329 | 0.134     | 36.82   |
| 0.368         | 16.0  | 2416 | 0.9141          | 0.16   | 0.0322 | 0.1268 | 0.1281    | 32.87   |
| 0.2635        | 17.0  | 2567 | 0.9177          | 0.1702 | 0.0324 | 0.1312 | 0.1323    | 35.4    |
| 0.2635        | 18.0  | 2718 | 0.9194          | 0.1713 | 0.0333 | 0.1297 | 0.1312    | 37.75   |
| 0.2635        | 19.0  | 2869 | 0.9234          | 0.1693 | 0.0294 | 0.1293 | 0.1299    | 35.69   |
| 0.2141        | 20.0  | 3020 | 0.9257          | 0.1655 | 0.0291 | 0.1256 | 0.1266    | 34.62   |


### Framework versions

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