---
license: apache-2.0
base_model: GanjinZero/biobart-v2-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-biobart-14-epochs
  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-14-epochs

This model is a fine-tuned version of [GanjinZero/biobart-v2-base](https://huggingface.co/GanjinZero/biobart-v2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7165
- Rouge1: 0.297
- Rouge2: 0.1097
- Rougel: 0.2649
- Rougelsum: 0.2663
- Gen Len: 14.74

## 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: 2e-05
- 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
- num_epochs: 14

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 151  | 0.7412          | 0.2238 | 0.0808 | 0.1984 | 0.2007    | 13.75   |
| No log        | 2.0   | 302  | 0.6979          | 0.2428 | 0.0841 | 0.2132 | 0.2156    | 13.26   |
| No log        | 3.0   | 453  | 0.6825          | 0.2488 | 0.0932 | 0.2216 | 0.2216    | 14.24   |
| 0.7256        | 4.0   | 604  | 0.6814          | 0.273  | 0.104  | 0.243  | 0.2442    | 13.94   |
| 0.7256        | 5.0   | 755  | 0.6845          | 0.2801 | 0.0999 | 0.2533 | 0.2542    | 14.2    |
| 0.7256        | 6.0   | 906  | 0.6837          | 0.2793 | 0.0997 | 0.253  | 0.2533    | 14.17   |
| 0.5118        | 7.0   | 1057 | 0.6941          | 0.2791 | 0.0988 | 0.2513 | 0.2517    | 14.62   |
| 0.5118        | 8.0   | 1208 | 0.6979          | 0.2968 | 0.1155 | 0.2677 | 0.2697    | 14.12   |
| 0.5118        | 9.0   | 1359 | 0.6983          | 0.2886 | 0.106  | 0.2633 | 0.2652    | 14.49   |
| 0.4062        | 10.0  | 1510 | 0.7048          | 0.2932 | 0.1117 | 0.2686 | 0.2714    | 14.36   |
| 0.4062        | 11.0  | 1661 | 0.7085          | 0.2773 | 0.1037 | 0.2512 | 0.2526    | 14.66   |
| 0.4062        | 12.0  | 1812 | 0.7140          | 0.2927 | 0.112  | 0.2657 | 0.2673    | 14.59   |
| 0.4062        | 13.0  | 1963 | 0.7162          | 0.2924 | 0.109  | 0.2597 | 0.262     | 14.57   |
| 0.3585        | 14.0  | 2114 | 0.7165          | 0.297  | 0.1097 | 0.2649 | 0.2663    | 14.74   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0