---
license: apache-2.0
base_model: moussaKam/AraBART
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: AraBART-finetuned-xlsum-ar
  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. -->

# AraBART-finetuned-xlsum-ar

This model is a fine-tuned version of [moussaKam/AraBART](https://huggingface.co/moussaKam/AraBART) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4655
- Rouge1: 24.4029
- Rouge2: 10.6961
- Rougel: 21.8597
- Rougelsum: 21.9193
- Gen Len: 19.6173

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.8881        | 1.0   | 2111  | 2.5078          | 23.0537 | 9.805   | 20.6712 | 20.7358   | 19.4371 |
| 2.7229        | 2.0   | 4222  | 2.4712          | 23.4792 | 10.0638 | 21.0179 | 21.0808   | 19.5933 |
| 2.6235        | 3.0   | 6333  | 2.4606          | 23.793  | 10.2551 | 21.2806 | 21.3525   | 19.5784 |
| 2.5475        | 4.0   | 8444  | 2.4557          | 23.8559 | 10.2547 | 21.3093 | 21.383    | 19.6013 |
| 2.4579        | 5.0   | 10555 | 2.4567          | 24.3906 | 10.6549 | 21.8215 | 21.8672   | 19.6471 |
| 2.4124        | 6.0   | 12666 | 2.4578          | 24.3648 | 10.6614 | 21.8584 | 21.9202   | 19.6018 |
| 2.38          | 7.0   | 14777 | 2.4606          | 24.3488 | 10.722  | 21.8546 | 21.9218   | 19.5938 |
| 2.3422        | 8.0   | 16888 | 2.4605          | 24.4836 | 10.7873 | 21.9424 | 21.9996   | 19.6215 |
| 2.3185        | 9.0   | 18999 | 2.4630          | 24.2878 | 10.6124 | 21.8332 | 21.8687   | 19.5949 |
| 2.2988        | 10.0  | 21110 | 2.4655          | 24.4029 | 10.6961 | 21.8597 | 21.9193   | 19.6173 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2