---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: pubmed-abs-sub-01
  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. -->

# pubmed-abs-sub-01

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0931

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.2288        | 0.11  | 500   | 0.1670          |
| 0.1744        | 0.21  | 1000  | 0.1545          |
| 0.1726        | 0.32  | 1500  | 0.1341          |
| 0.1622        | 0.43  | 2000  | 0.1329          |
| 0.1382        | 0.54  | 2500  | 0.1289          |
| 0.1322        | 0.64  | 3000  | 0.1184          |
| 0.1288        | 0.75  | 3500  | 0.1182          |
| 0.1304        | 0.86  | 4000  | 0.1088          |
| 0.1255        | 0.96  | 4500  | 0.1068          |
| 0.1039        | 1.07  | 5000  | 0.1093          |
| 0.0969        | 1.18  | 5500  | 0.1060          |
| 0.1001        | 1.28  | 6000  | 0.1087          |
| 0.0966        | 1.39  | 6500  | 0.1027          |
| 0.101         | 1.5   | 7000  | 0.0999          |
| 0.0851        | 1.61  | 7500  | 0.1010          |
| 0.1068        | 1.71  | 8000  | 0.1021          |
| 0.1024        | 1.82  | 8500  | 0.0966          |
| 0.0852        | 1.93  | 9000  | 0.0962          |
| 0.0688        | 2.03  | 9500  | 0.0967          |
| 0.0791        | 2.14  | 10000 | 0.0987          |
| 0.0606        | 2.25  | 10500 | 0.0978          |
| 0.0732        | 2.35  | 11000 | 0.0963          |
| 0.0758        | 2.46  | 11500 | 0.0951          |
| 0.0765        | 2.57  | 12000 | 0.0945          |
| 0.0671        | 2.68  | 12500 | 0.0932          |
| 0.0422        | 2.78  | 13000 | 0.0936          |
| 0.0493        | 2.89  | 13500 | 0.0942          |
| 0.0542        | 3.0   | 14000 | 0.0931          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1