---
license: apache-2.0
base_model: GanjinZero/biobart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-BioBART-20-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-20-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: 1.6050
- Rouge1: 0.1704
- Rouge2: 0.0496
- Rougel: 0.138
- Rougelsum: 0.1356
- Gen Len: 34.1

## 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  | 6.5303          | 0.0    | 0.0    | 0.0    | 0.0       | 12.58   |
| No log        | 2.0   | 302  | 1.9967          | 0.1046 | 0.0318 | 0.0908 | 0.0904    | 26.22   |
| No log        | 3.0   | 453  | 1.6736          | 0.0447 | 0.0076 | 0.036  | 0.0353    | 15.66   |
| 4.5402        | 4.0   | 604  | 1.5728          | 0.1397 | 0.0344 | 0.1068 | 0.1079    | 34.51   |
| 4.5402        | 5.0   | 755  | 1.5231          | 0.1675 | 0.0345 | 0.1325 | 0.1328    | 34.4    |
| 4.5402        | 6.0   | 906  | 1.4986          | 0.1195 | 0.0287 | 0.0863 | 0.0873    | 38.66   |
| 1.1958        | 7.0   | 1057 | 1.4791          | 0.1478 | 0.0379 | 0.1172 | 0.1176    | 35.41   |
| 1.1958        | 8.0   | 1208 | 1.4802          | 0.1459 | 0.0368 | 0.1066 | 0.108     | 32.5    |
| 1.1958        | 9.0   | 1359 | 1.4841          | 0.1687 | 0.0289 | 0.1342 | 0.1345    | 30.89   |
| 0.7933        | 10.0  | 1510 | 1.5005          | 0.1457 | 0.035  | 0.1125 | 0.1103    | 34.3    |
| 0.7933        | 11.0  | 1661 | 1.5101          | 0.1808 | 0.0364 | 0.1498 | 0.1505    | 31.33   |
| 0.7933        | 12.0  | 1812 | 1.5262          | 0.1882 | 0.0419 | 0.1553 | 0.1549    | 31.65   |
| 0.7933        | 13.0  | 1963 | 1.5481          | 0.167  | 0.032  | 0.1381 | 0.139     | 31.04   |
| 0.5232        | 14.0  | 2114 | 1.5494          | 0.1723 | 0.0442 | 0.1407 | 0.138     | 34.88   |
| 0.5232        | 15.0  | 2265 | 1.5590          | 0.1801 | 0.0318 | 0.142  | 0.1413    | 37.99   |
| 0.5232        | 16.0  | 2416 | 1.5829          | 0.1608 | 0.0353 | 0.1249 | 0.1249    | 33.97   |
| 0.3565        | 17.0  | 2567 | 1.5837          | 0.1535 | 0.0354 | 0.1159 | 0.115     | 35.96   |
| 0.3565        | 18.0  | 2718 | 1.5977          | 0.1565 | 0.0349 | 0.1244 | 0.1227    | 34.29   |
| 0.3565        | 19.0  | 2869 | 1.6002          | 0.169  | 0.0428 | 0.1358 | 0.1331    | 34.84   |
| 0.2734        | 20.0  | 3020 | 1.6050          | 0.1704 | 0.0496 | 0.138  | 0.1356    | 34.1    |


### Framework versions

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