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-15-epochs-1024-input-128-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-15-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: 1.5422
- Rouge1: 0.1912
- Rouge2: 0.042
- Rougel: 0.1492
- Rougelsum: 0.15
- Gen Len: 29.97

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 151  | 5.4038          | 0.0026 | 0.0006 | 0.0024 | 0.0024    | 5.98    |
| No log        | 2.0   | 302  | 1.8682          | 0.0475 | 0.0066 | 0.0452 | 0.043     | 6.59    |
| No log        | 3.0   | 453  | 1.6512          | 0.0753 | 0.0169 | 0.0587 | 0.0586    | 22.62   |
| 4.1375        | 4.0   | 604  | 1.5702          | 0.1472 | 0.0366 | 0.1124 | 0.1113    | 42.92   |
| 4.1375        | 5.0   | 755  | 1.5256          | 0.167  | 0.0337 | 0.1309 | 0.1305    | 45.89   |
| 4.1375        | 6.0   | 906  | 1.5057          | 0.1435 | 0.0305 | 0.1132 | 0.1134    | 32.45   |
| 1.1893        | 7.0   | 1057 | 1.4854          | 0.1655 | 0.0388 | 0.129  | 0.1295    | 34.34   |
| 1.1893        | 8.0   | 1208 | 1.4845          | 0.1635 | 0.0423 | 0.1238 | 0.1252    | 37.77   |
| 1.1893        | 9.0   | 1359 | 1.4980          | 0.1712 | 0.0363 | 0.1382 | 0.1388    | 29.68   |
| 0.8262        | 10.0  | 1510 | 1.5052          | 0.1917 | 0.0431 | 0.1486 | 0.1497    | 32.88   |
| 0.8262        | 11.0  | 1661 | 1.5167          | 0.1731 | 0.0374 | 0.1402 | 0.1403    | 29.9    |
| 0.8262        | 12.0  | 1812 | 1.5267          | 0.1675 | 0.035  | 0.1335 | 0.1337    | 29.35   |
| 0.8262        | 13.0  | 1963 | 1.5329          | 0.1839 | 0.0401 | 0.1465 | 0.1465    | 28.23   |
| 0.61          | 14.0  | 2114 | 1.5440          | 0.1904 | 0.0452 | 0.1522 | 0.1527    | 29.33   |
| 0.61          | 15.0  | 2265 | 1.5422          | 0.1912 | 0.042  | 0.1492 | 0.15      | 29.97   |


### Framework versions

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