---
library_name: peft
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 7.6783
- Rouge1: 22.6282
- Rouge2: 2.7613
- Rougel: 15.7792
- Gen Len: 66.1839

## 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
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Gen Len  |
|:-------------:|:------:|:----:|:---------------:|:-------:|:------:|:-------:|:--------:|
| 7.8707        | 0.5754 | 500  | 7.7020          | 22.5587 | 2.5824 | 15.5739 | 64.7494  |
| 7.7352        | 1.1507 | 1000 | 7.4834          | 22.4958 | 2.3149 | 15.6863 | 69.8138  |
| 7.2829        | 1.7261 | 1500 | 6.9061          | 20.4987 | 2.3443 | 15.3680 | 98.8828  |
| 7.0328        | 2.3015 | 2000 | 6.9069          | 20.6740 | 2.2923 | 15.6237 | 108.1402 |
| 6.9828        | 2.8769 | 2500 | 6.8401          | 21.0086 | 2.2733 | 15.7925 | 106.2667 |


### Framework versions

- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0