---
library_name: peft
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart_lora_finetune
  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_lora_finetune

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: 1.8519
- Rouge1: 0.422
- Rouge2: 0.193
- Rougel: 0.2864
- Rougelsum: 0.3929
- Gen Len: 89.8971

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:------:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.2909        | 0.2786 | 10000 | 1.9040          | 0.4197 | 0.1915 | 0.2803 | 0.39      | 95.844  |
| 2.2169        | 0.5573 | 20000 | 1.8850          | 0.4166 | 0.1886 | 0.2831 | 0.3876    | 86.0059 |
| 2.1929        | 0.8359 | 30000 | 1.8784          | 0.4213 | 0.192  | 0.2858 | 0.391     | 86.0011 |
| 2.1806        | 1.1145 | 40000 | 1.8755          | 0.419  | 0.1905 | 0.2829 | 0.3892    | 91.4016 |
| 2.1683        | 1.3931 | 50000 | 1.8673          | 0.4202 | 0.1916 | 0.2834 | 0.3916    | 94.264  |
| 2.164         | 1.6718 | 60000 | 1.8603          | 0.4214 | 0.1923 | 0.2846 | 0.3919    | 90.9084 |
| 2.1594        | 1.9504 | 70000 | 1.8519          | 0.422  | 0.193  | 0.2864 | 0.3929    | 89.8971 |


### Framework versions

- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.6.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1