---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: pubmed-abs-noise-04
  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-04

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: 0.5519

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.9533        | 0.11  | 500   | 0.7930          |
| 0.8667        | 0.21  | 1000  | 0.7234          |
| 0.797         | 0.32  | 1500  | 0.6901          |
| 0.7887        | 0.43  | 2000  | 0.6696          |
| 0.7616        | 0.54  | 2500  | 0.6600          |
| 0.6708        | 0.64  | 3000  | 0.6435          |
| 0.6794        | 0.75  | 3500  | 0.6287          |
| 0.6342        | 0.86  | 4000  | 0.6163          |
| 0.6815        | 0.96  | 4500  | 0.6073          |
| 0.6312        | 1.07  | 5000  | 0.6038          |
| 0.5506        | 1.18  | 5500  | 0.5975          |
| 0.5828        | 1.28  | 6000  | 0.5972          |
| 0.5568        | 1.39  | 6500  | 0.5920          |
| 0.5834        | 1.5   | 7000  | 0.5809          |
| 0.5236        | 1.61  | 7500  | 0.5808          |
| 0.5446        | 1.71  | 8000  | 0.5727          |
| 0.5838        | 1.82  | 8500  | 0.5691          |
| 0.5038        | 1.93  | 9000  | 0.5628          |
| 0.469         | 2.03  | 9500  | 0.5687          |
| 0.4529        | 2.14  | 10000 | 0.5673          |
| 0.4987        | 2.25  | 10500 | 0.5614          |
| 0.4471        | 2.35  | 11000 | 0.5621          |
| 0.4831        | 2.46  | 11500 | 0.5569          |
| 0.4683        | 2.57  | 12000 | 0.5565          |
| 0.4547        | 2.68  | 12500 | 0.5562          |
| 0.4346        | 2.78  | 13000 | 0.5543          |
| 0.47          | 2.89  | 13500 | 0.5534          |
| 0.4144        | 3.0   | 14000 | 0.5519          |


### Framework versions

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