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---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- xlsum
model-index:
- name: AraBART-finetune-ar-xlsum
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-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: 3.7449
- Rouge-1: 31.08
- Rouge-2: 14.68
- Rouge-l: 27.36
- Gen Len: 19.64
- Bertscore: 73.86
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 10
- label_smoothing_factor: 0.1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
| 4.4318 | 1.0 | 2345 | 3.7996 | 28.93 | 13.2 | 25.56 | 19.51 | 73.17 |
| 4.0338 | 2.0 | 4690 | 3.7483 | 30.29 | 14.24 | 26.73 | 19.5 | 73.59 |
| 3.8586 | 3.0 | 7035 | 3.7281 | 30.44 | 14.44 | 26.92 | 19.75 | 73.58 |
| 3.7289 | 4.0 | 9380 | 3.7204 | 30.55 | 14.49 | 26.88 | 19.66 | 73.73 |
| 3.6245 | 5.0 | 11725 | 3.7199 | 30.73 | 14.63 | 27.11 | 19.69 | 73.68 |
| 3.5392 | 6.0 | 14070 | 3.7221 | 30.85 | 14.65 | 27.21 | 19.7 | 73.77 |
| 3.4694 | 7.0 | 16415 | 3.7286 | 31.08 | 14.8 | 27.41 | 19.62 | 73.84 |
| 3.4126 | 8.0 | 18760 | 3.7384 | 31.06 | 14.77 | 27.41 | 19.64 | 73.82 |
| 3.3718 | 9.0 | 21105 | 3.7398 | 31.18 | 14.89 | 27.49 | 19.67 | 73.87 |
| 3.3428 | 10.0 | 23450 | 3.7449 | 31.19 | 14.88 | 27.44 | 19.68 | 73.87 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
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