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---
tags:
- summarization
- generated_from_trainer
datasets:
- wiki_lingua
model-index:
- name: mbart-large-50-finetuned-ar-wikilingua
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. -->
# mbart-large-50-finetuned-ar-wikilingua
This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the wiki_lingua dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0001
- Rouge-1: 22.11
- Rouge-2: 7.33
- Rouge-l: 19.75
- Gen Len: 59.4
- Bertscore: 68.9
## 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: 1e-06
- train_batch_size: 4
- eval_batch_size: 4
- 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: 8
- label_smoothing_factor: 0.1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
| 5.2671 | 1.0 | 5111 | 4.6414 | 18.37 | 5.63 | 16.32 | 96.39 | 65.12 |
| 4.5375 | 2.0 | 10222 | 4.3144 | 20.49 | 6.64 | 18.35 | 95.44 | 65.79 |
| 4.308 | 3.0 | 15333 | 4.1592 | 21.16 | 7.09 | 18.85 | 67.75 | 67.65 |
| 4.1562 | 4.0 | 20444 | 4.0812 | 21.59 | 7.31 | 19.42 | 68.66 | 68.02 |
| 4.0749 | 5.0 | 25555 | 4.0409 | 21.99 | 7.42 | 19.82 | 66.4 | 68.05 |
| 4.0271 | 6.0 | 30666 | 4.0183 | 22.04 | 7.42 | 19.64 | 56.88 | 68.95 |
| 3.9991 | 7.0 | 35777 | 4.0042 | 22.05 | 7.35 | 19.71 | 55.75 | 68.94 |
| 3.9833 | 8.0 | 40888 | 4.0001 | 22.12 | 7.39 | 19.78 | 55.72 | 69.0 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
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