---
license: mit
base_model: facebook/bart-large-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-xsum-dc
  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-large-xsum-dc

This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6335
- Rouge1: 32.0323
- Rouge2: 14.1008
- Rougel: 24.5596
- Rougelsum: 25.6498

## 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: 5.6e-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

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 1.9052        | 1.0   | 2676  | 1.7569          | 30.4785 | 12.762  | 23.1862 | 23.9824   |
| 1.4258        | 2.0   | 5352  | 1.5930          | 31.7087 | 13.5933 | 23.9115 | 24.7093   |
| 1.1141        | 3.0   | 8028  | 1.5729          | 32.3123 | 14.3572 | 24.8666 | 25.856    |
| 0.8621        | 4.0   | 10704 | 1.6335          | 32.0323 | 14.1008 | 24.5596 | 25.6498   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2