---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: BART1
  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. -->

# BART1

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8706
- Rouge1: 57.2472
- Rouge2: 23.1787
- Rougel: 41.8726
- Rougelsum: 53.8183
- Gen Len: 234.4232

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 5.8303        | 0.0835 | 100  | 5.6762          | 48.0404 | 16.526  | 33.0315 | 45.2714   | 234.4232 |
| 5.2419        | 0.1671 | 200  | 5.1330          | 49.5121 | 17.8978 | 34.5708 | 46.291    | 234.4232 |
| 5.0085        | 0.2506 | 300  | 4.8037          | 52.3507 | 19.2179 | 36.3445 | 48.7473   | 234.4232 |
| 4.676         | 0.3342 | 400  | 4.5745          | 51.4939 | 19.2534 | 37.2441 | 48.7288   | 234.4232 |
| 4.4521        | 0.4177 | 500  | 4.4154          | 52.9389 | 20.2028 | 38.4139 | 49.9981   | 234.4232 |
| 4.4572        | 0.5013 | 600  | 4.2389          | 54.6029 | 21.0796 | 39.2355 | 51.1397   | 234.4232 |
| 4.2836        | 0.5848 | 700  | 4.1267          | 55.5174 | 22.1184 | 40.2744 | 52.0886   | 234.4232 |
| 4.2862        | 0.6684 | 800  | 4.0549          | 56.305  | 22.433  | 40.8636 | 52.6987   | 234.4232 |
| 4.0806        | 0.7519 | 900  | 3.9673          | 57.3033 | 22.873  | 41.2543 | 53.5936   | 234.4232 |
| 4.0806        | 0.8355 | 1000 | 3.9154          | 56.3519 | 22.7588 | 41.4512 | 52.9385   | 234.4232 |
| 3.8885        | 0.9190 | 1100 | 3.8706          | 57.2472 | 23.1787 | 41.8726 | 53.8183   | 234.4232 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1