---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: pubmed-abs-ins-con-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-ins-con-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: 0.0594

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.1805        | 0.11  | 500   | 0.1197          |
| 0.1078        | 0.21  | 1000  | 0.0990          |
| 0.126         | 0.32  | 1500  | 0.0879          |
| 0.1501        | 0.43  | 2000  | 0.0806          |
| 0.0957        | 0.54  | 2500  | 0.0849          |
| 0.1111        | 0.64  | 3000  | 0.0765          |
| 0.0942        | 0.75  | 3500  | 0.0785          |
| 0.0897        | 0.86  | 4000  | 0.0703          |
| 0.0867        | 0.96  | 4500  | 0.0701          |
| 0.0838        | 1.07  | 5000  | 0.0711          |
| 0.0757        | 1.18  | 5500  | 0.0673          |
| 0.0586        | 1.28  | 6000  | 0.0759          |
| 0.0701        | 1.39  | 6500  | 0.0648          |
| 0.0655        | 1.5   | 7000  | 0.0652          |
| 0.0569        | 1.61  | 7500  | 0.0667          |
| 0.0564        | 1.71  | 8000  | 0.0650          |
| 0.1031        | 1.82  | 8500  | 0.0631          |
| 0.0701        | 1.93  | 9000  | 0.0590          |
| 0.0612        | 2.03  | 9500  | 0.0625          |
| 0.0576        | 2.14  | 10000 | 0.0627          |
| 0.048         | 2.25  | 10500 | 0.0617          |
| 0.044         | 2.35  | 11000 | 0.0616          |
| 0.0459        | 2.46  | 11500 | 0.0605          |
| 0.0546        | 2.57  | 12000 | 0.0588          |
| 0.0533        | 2.68  | 12500 | 0.0589          |
| 0.0354        | 2.78  | 13000 | 0.0592          |
| 0.0366        | 2.89  | 13500 | 0.0606          |
| 0.0436        | 3.0   | 14000 | 0.0594          |


### Framework versions

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