---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: Bart-base-v1
  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-base-v1

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: 0.0391

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.0951        | 0.32  | 250  | 0.0443          |
| 0.051         | 0.64  | 500  | 0.0424          |
| 0.0493        | 0.96  | 750  | 0.0409          |
| 0.0441        | 1.28  | 1000 | 0.0401          |
| 0.0428        | 1.61  | 1250 | 0.0399          |
| 0.0426        | 1.93  | 1500 | 0.0393          |
| 0.0394        | 2.25  | 1750 | 0.0397          |
| 0.0382        | 2.57  | 2000 | 0.0390          |
| 0.038         | 2.89  | 2250 | 0.0389          |
| 0.0356        | 3.21  | 2500 | 0.0393          |
| 0.0347        | 3.53  | 2750 | 0.0392          |
| 0.0343        | 3.85  | 3000 | 0.0390          |
| 0.0331        | 4.17  | 3250 | 0.0392          |
| 0.0313        | 4.49  | 3500 | 0.0393          |
| 0.0319        | 4.82  | 3750 | 0.0390          |
| 0.0307        | 5.14  | 4000 | 0.0392          |
| 0.0296        | 5.46  | 4250 | 0.0394          |
| 0.0297        | 5.78  | 4500 | 0.0391          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.15.2