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---
license: apache-2.0
metrics:
- rouge
model-index:
- name: AraBART-finetuned-wiki-ar
results: []
pipeline_tag: translation
---
<!-- 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-wiki-ar
This model is a fine-tuned version of [moussaKam/AraBART](https://huggingface.co/moussaKam/AraBART) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4030
- Rouge1: 0.9862
- Rouge2: 0.2292
- Rougel: 0.9902
- Rougelsum: 0.9847
- Gen Len: 19.3511
## 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: 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: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.8633 | 1.0 | 2556 | 2.5599 | 0.7861 | 0.1289 | 0.7656 | 0.7721 | 19.2354 |
| 2.6525 | 2.0 | 5112 | 2.4824 | 0.7315 | 0.2374 | 0.7224 | 0.7357 | 19.261 |
| 2.5068 | 3.0 | 7668 | 2.4404 | 0.7772 | 0.2114 | 0.7671 | 0.7861 | 19.3035 |
| 2.4251 | 4.0 | 10224 | 2.4269 | 0.7464 | 0.2156 | 0.745 | 0.7504 | 19.2929 |
| 2.3739 | 5.0 | 12780 | 2.4119 | 0.7642 | 0.1879 | 0.7729 | 0.7774 | 19.3573 |
| 2.275 | 6.0 | 15336 | 2.4039 | 0.9048 | 0.1952 | 0.9198 | 0.9189 | 19.37 |
| 2.2787 | 7.0 | 17892 | 2.4007 | 0.9913 | 0.2278 | 0.9951 | 1.0038 | 19.335 |
| 2.2142 | 8.0 | 20448 | 2.4073 | 0.9736 | 0.238 | 0.9697 | 0.9773 | 19.3556 |
| 2.1852 | 9.0 | 23004 | 2.4007 | 0.9825 | 0.2322 | 0.9891 | 0.9962 | 19.3213 |
| 2.1597 | 10.0 | 25560 | 2.4030 | 0.9862 | 0.2292 | 0.9902 | 0.9847 | 19.3511 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2 |