---
license: mit
tags:
- generated_from_trainer
- summarization
datasets:
- orange_sum
model-index:
- name: BART-CNN-Orangesum
  results: []
language:
- fr
- en
---

# BART-CNN-Orangesum

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the orange_sum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6370

It aims at improving the quality of the summary generated on French texts

## Model description

this is a fine tuning of the model 'facebook/bart-large-cnn' on the 'orange_sum' dataset
gives better results in French while keeping the intrinsic qualities of the BART model

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.9062        | 0.37  | 500  | 1.8412          |
| 1.6596        | 0.75  | 1000 | 1.6370          |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3