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-1500-input-256-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-1500-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: 0.8909
- Rouge1: 0.1801
- Rouge2: 0.0468
- Rougel: 0.1405
- Rougelsum: 0.1403
- Gen Len: 36.53

## 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: 4
- eval_batch_size: 4
- 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   | 301  | 1.4869          | 0.086  | 0.0035 | 0.0743 | 0.0744    | 10.36   |
| 4.753         | 2.0   | 602  | 0.9880          | 0.0958 | 0.0233 | 0.0687 | 0.0686    | 47.88   |
| 4.753         | 3.0   | 903  | 0.9108          | 0.0622 | 0.009  | 0.0617 | 0.0622    | 10.39   |
| 0.9239        | 4.0   | 1204 | 0.8681          | 0.1159 | 0.0272 | 0.085  | 0.0849    | 27.95   |
| 0.7513        | 5.0   | 1505 | 0.8490          | 0.1732 | 0.0333 | 0.1345 | 0.1352    | 37.9    |
| 0.7513        | 6.0   | 1806 | 0.8486          | 0.1523 | 0.0297 | 0.12   | 0.1209    | 33.96   |
| 0.5751        | 7.0   | 2107 | 0.8402          | 0.1825 | 0.0426 | 0.1433 | 0.1437    | 40.27   |
| 0.5751        | 8.0   | 2408 | 0.8500          | 0.1712 | 0.0303 | 0.1425 | 0.1427    | 31.42   |
| 0.4702        | 9.0   | 2709 | 0.8542          | 0.1764 | 0.0325 | 0.1275 | 0.1273    | 44.93   |
| 0.3782        | 10.0  | 3010 | 0.8615          | 0.1667 | 0.042  | 0.1328 | 0.1335    | 36.86   |
| 0.3782        | 11.0  | 3311 | 0.8714          | 0.1756 | 0.0358 | 0.1364 | 0.1359    | 35.21   |
| 0.3005        | 12.0  | 3612 | 0.8772          | 0.1801 | 0.0368 | 0.1427 | 0.1427    | 33.99   |
| 0.3005        | 13.0  | 3913 | 0.8818          | 0.1685 | 0.0397 | 0.1323 | 0.1331    | 34.67   |
| 0.2417        | 14.0  | 4214 | 0.8891          | 0.189  | 0.0495 | 0.145  | 0.1445    | 36.0    |
| 0.2148        | 15.0  | 4515 | 0.8909          | 0.1801 | 0.0468 | 0.1405 | 0.1403    | 36.53   |


### Framework versions

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