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-10-epochs-1024-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-10-epochs-1024-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: 0.8636
- Rouge1: 0.1803
- Rouge2: 0.043
- Rougel: 0.1391
- Rougelsum: 0.1408
- Gen Len: 39.35

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 151  | 2.4893          | 0.0    | 0.0    | 0.0    | 0.0       | 4.56    |
| No log        | 2.0   | 302  | 1.0370          | 0.1382 | 0.033  | 0.1174 | 0.1192    | 28.23   |
| No log        | 3.0   | 453  | 0.9481          | 0.0912 | 0.0231 | 0.0723 | 0.072     | 22.01   |
| 3.1525        | 4.0   | 604  | 0.9079          | 0.1402 | 0.0336 | 0.1063 | 0.1064    | 42.37   |
| 3.1525        | 5.0   | 755  | 0.8861          | 0.1772 | 0.0335 | 0.1344 | 0.1364    | 49.96   |
| 3.1525        | 6.0   | 906  | 0.8760          | 0.1702 | 0.0327 | 0.1301 | 0.1313    | 42.56   |
| 0.7557        | 7.0   | 1057 | 0.8661          | 0.158  | 0.0403 | 0.1136 | 0.114     | 40.53   |
| 0.7557        | 8.0   | 1208 | 0.8641          | 0.1631 | 0.0431 | 0.119  | 0.1198    | 44.57   |
| 0.7557        | 9.0   | 1359 | 0.8659          | 0.172  | 0.0427 | 0.1357 | 0.1369    | 38.31   |
| 0.5883        | 10.0  | 1510 | 0.8636          | 0.1803 | 0.043  | 0.1391 | 0.1408    | 39.35   |


### Framework versions

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