---
library_name: peft
license: apache-2.0
base_model: GanjinZero/biobart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: biobart-finetune
  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. -->

# biobart-finetune

This model is a fine-tuned version of [GanjinZero/biobart-base](https://huggingface.co/GanjinZero/biobart-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9186
- Rouge1: 22.5525
- Rouge2: 4.3362
- Rougel: 15.8156
- Rougelsum: 19.1059
- Gen Len: 42.9050

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 6.4594        | 0.2252 | 100  | 6.4329          | 18.9117 | 2.0188 | 11.7200 | 14.0691   | 87.4745 |
| 4.9261        | 0.4505 | 200  | 4.3777          | 18.5212 | 2.0711 | 11.6242 | 13.9036   | 93.2281 |
| 3.7235        | 0.6757 | 300  | 3.4460          | 17.5924 | 2.6991 | 12.4698 | 13.9427   | 31.1940 |
| 3.5392        | 0.9009 | 400  | 3.2915          | 17.2541 | 2.7861 | 12.9556 | 14.3577   | 21.3399 |
| 3.3947        | 1.1261 | 500  | 3.1847          | 17.2388 | 2.8528 | 13.0146 | 14.3760   | 19.3028 |
| 3.3591        | 1.3514 | 600  | 3.1129          | 17.9652 | 3.0939 | 13.4691 | 14.8890   | 20.4810 |
| 3.2893        | 1.5766 | 700  | 3.0270          | 19.5473 | 3.3778 | 14.3209 | 16.0940   | 25.6393 |
| 3.2196        | 1.8018 | 800  | 2.9678          | 21.1542 | 3.9248 | 15.1733 | 17.7524   | 32.2133 |
| 3.1616        | 2.0270 | 900  | 2.9470          | 22.2155 | 4.3290 | 15.6293 | 18.7960   | 41.2048 |
| 3.1339        | 2.2523 | 1000 | 2.9354          | 22.5585 | 4.2939 | 15.5387 | 19.1468   | 47.4577 |
| 3.1307        | 2.4775 | 1100 | 2.9255          | 22.6986 | 4.3846 | 15.8222 | 19.2784   | 44.6423 |
| 3.1409        | 2.7027 | 1200 | 2.9202          | 22.7305 | 4.3966 | 15.8445 | 19.2561   | 43.9401 |
| 3.1098        | 2.9279 | 1300 | 2.9186          | 22.5525 | 4.3362 | 15.8156 | 19.1059   | 42.9050 |


### Framework versions

- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0