---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: PTS-Bart-Large-CNN
  results: []
pipeline_tag: summarization
---

<!-- 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. -->

# PTS-Bart-Large-CNN

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co./facebook/bart-large-cnn) on the PTS dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0177
- Rouge1: 0.6339
- Rouge2: 0.4113
- Rougel: 0.5344
- Rougelsum: 0.5338
- Gen Len: 76.1278

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 180  | 0.9026          | 0.6109 | 0.3819 | 0.5098 | 0.5094    | 76.9722 |
| No log        | 2.0   | 360  | 0.9012          | 0.6273 | 0.4054 | 0.5285 | 0.5284    | 76.3833 |
| 0.6717        | 3.0   | 540  | 0.9357          | 0.6312 | 0.4071 | 0.5297 | 0.5295    | 76.25   |
| 0.6717        | 4.0   | 720  | 1.0177          | 0.6339 | 0.4113 | 0.5344 | 0.5338    | 76.1278 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1