---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: bart-noised-with-gcd-dist-0.3
  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. -->

# bart-noised-with-gcd-dist-0.3

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: 1.0832

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.4395        | 0.11  | 500   | 1.3691          |
| 1.4568        | 0.21  | 1000  | 1.3068          |
| 1.3702        | 0.32  | 1500  | 1.2510          |
| 1.2945        | 0.43  | 2000  | 1.2319          |
| 1.3022        | 0.54  | 2500  | 1.2092          |
| 1.1775        | 0.64  | 3000  | 1.2022          |
| 1.1657        | 0.75  | 3500  | 1.1822          |
| 1.1756        | 0.86  | 4000  | 1.1823          |
| 1.2103        | 0.96  | 4500  | 1.1521          |
| 1.1467        | 1.07  | 5000  | 1.1535          |
| 1.0617        | 1.18  | 5500  | 1.1443          |
| 1.0667        | 1.28  | 6000  | 1.1339          |
| 1.0906        | 1.39  | 6500  | 1.1369          |
| 1.0492        | 1.5   | 7000  | 1.1213          |
| 1.0203        | 1.61  | 7500  | 1.1207          |
| 0.9431        | 1.71  | 8000  | 1.1183          |
| 1.0522        | 1.82  | 8500  | 1.1052          |
| 1.0673        | 1.93  | 9000  | 1.0996          |
| 0.9521        | 2.03  | 9500  | 1.1079          |
| 0.9615        | 2.14  | 10000 | 1.0990          |
| 0.996         | 2.25  | 10500 | 1.0976          |
| 0.9458        | 2.35  | 11000 | 1.0997          |
| 0.9375        | 2.46  | 11500 | 1.0939          |
| 0.8869        | 2.57  | 12000 | 1.0896          |
| 0.8934        | 2.68  | 12500 | 1.0895          |
| 0.8561        | 2.78  | 13000 | 1.0839          |
| 0.9795        | 2.89  | 13500 | 1.0834          |
| 0.8886        | 3.0   | 14000 | 1.0832          |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1