---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: AraBART-finetuned-ar
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xlsum
      type: xlsum
      args: arabic
    metrics:
    - name: Rouge1
      type: rouge
      value: 2.2459
---

<!-- 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-ar

This model is a fine-tuned version of [moussaKam/AraBART](https://huggingface.co/moussaKam/AraBART) on the xlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3785
- Rouge1: 2.2459
- Rouge2: 0.0
- Rougel: 2.2459
- Rougelsum: 2.2459
- Gen Len: 19.695

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.6
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 0.98  | 32   | 2.7774          | 1.0638 | 0.0    | 1.0638 | 1.182     | 19.5177 |
| No log        | 1.98  | 64   | 2.4730          | 1.182  | 0.0    | 1.3002 | 1.182     | 19.8121 |
| No log        | 2.98  | 96   | 2.4129          | 2.3641 | 0.3546 | 2.3641 | 2.3641    | 19.8298 |
| No log        | 3.98  | 128  | 2.3724          | 2.1277 | 0.3546 | 2.1277 | 2.1277    | 19.8121 |
| No log        | 4.98  | 160  | 2.3560          | 1.8913 | 0.3546 | 1.8913 | 1.8913    | 19.805  |
| No log        | 5.98  | 192  | 2.3574          | 1.5366 | 0.0    | 1.5366 | 1.6548    | 19.7979 |
| No log        | 6.98  | 224  | 2.3676          | 2.1277 | 0.3546 | 2.2459 | 2.1277    | 19.6348 |
| No log        | 7.98  | 256  | 2.3656          | 2.0095 | 0.0    | 2.0095 | 2.0095    | 19.844  |
| No log        | 8.98  | 288  | 2.3751          | 2.2459 | 0.0    | 2.3641 | 2.2459    | 19.6738 |
| No log        | 9.98  | 320  | 2.3785          | 2.2459 | 0.0    | 2.2459 | 2.2459    | 19.695  |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6