---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: pubmed-abs-noise-05
  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-noise-05

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: 0.6496

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.092         | 0.11  | 500   | 0.9325          |
| 0.9641        | 0.21  | 1000  | 0.8608          |
| 1.0013        | 0.32  | 1500  | 0.8162          |
| 0.9596        | 0.43  | 2000  | 0.7818          |
| 0.8598        | 0.54  | 2500  | 0.7740          |
| 0.7675        | 0.64  | 3000  | 0.7710          |
| 0.7932        | 0.75  | 3500  | 0.7411          |
| 0.766         | 0.86  | 4000  | 0.7280          |
| 0.7806        | 0.96  | 4500  | 0.7130          |
| 0.7571        | 1.07  | 5000  | 0.7091          |
| 0.6968        | 1.18  | 5500  | 0.7011          |
| 0.6832        | 1.28  | 6000  | 0.6986          |
| 0.674         | 1.39  | 6500  | 0.6935          |
| 0.6475        | 1.5   | 7000  | 0.6829          |
| 0.6876        | 1.61  | 7500  | 0.6798          |
| 0.6355        | 1.71  | 8000  | 0.6745          |
| 0.6788        | 1.82  | 8500  | 0.6717          |
| 0.62          | 1.93  | 9000  | 0.6692          |
| 0.5702        | 2.03  | 9500  | 0.6697          |
| 0.6105        | 2.14  | 10000 | 0.6665          |
| 0.5658        | 2.25  | 10500 | 0.6646          |
| 0.5826        | 2.35  | 11000 | 0.6630          |
| 0.5342        | 2.46  | 11500 | 0.6558          |
| 0.5624        | 2.57  | 12000 | 0.6560          |
| 0.5659        | 2.68  | 12500 | 0.6526          |
| 0.5328        | 2.78  | 13000 | 0.6514          |
| 0.5268        | 2.89  | 13500 | 0.6501          |
| 0.5536        | 3.0   | 14000 | 0.6496          |


### Framework versions

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