---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: pubmed-abs-ins-con-03
  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-ins-con-03

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: 0.0608

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.2122        | 0.11  | 500   | 0.1152          |
| 0.1463        | 0.21  | 1000  | 0.1051          |
| 0.1388        | 0.32  | 1500  | 0.0947          |
| 0.2079        | 0.43  | 2000  | 0.0869          |
| 0.1049        | 0.54  | 2500  | 0.0875          |
| 0.1135        | 0.64  | 3000  | 0.0802          |
| 0.1019        | 0.75  | 3500  | 0.0747          |
| 0.1079        | 0.86  | 4000  | 0.0731          |
| 0.0999        | 0.96  | 4500  | 0.0691          |
| 0.0792        | 1.07  | 5000  | 0.0723          |
| 0.0728        | 1.18  | 5500  | 0.0729          |
| 0.0802        | 1.28  | 6000  | 0.0733          |
| 0.066         | 1.39  | 6500  | 0.0683          |
| 0.0788        | 1.5   | 7000  | 0.0681          |
| 0.0656        | 1.61  | 7500  | 0.0692          |
| 0.061         | 1.71  | 8000  | 0.0670          |
| 0.1196        | 1.82  | 8500  | 0.0629          |
| 0.0687        | 1.93  | 9000  | 0.0620          |
| 0.0586        | 2.03  | 9500  | 0.0639          |
| 0.0646        | 2.14  | 10000 | 0.0645          |
| 0.0456        | 2.25  | 10500 | 0.0651          |
| 0.0502        | 2.35  | 11000 | 0.0636          |
| 0.0505        | 2.46  | 11500 | 0.0625          |
| 0.0633        | 2.57  | 12000 | 0.0603          |
| 0.0514        | 2.68  | 12500 | 0.0603          |
| 0.0421        | 2.78  | 13000 | 0.0613          |
| 0.0407        | 2.89  | 13500 | 0.0607          |
| 0.0436        | 3.0   | 14000 | 0.0608          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.7
- Tokenizers 0.14.1