README.md

---
tags:
- generated_from_trainer
metrics:
- rouge
base_model: malmarjeh/mbert2mbert-arabic-text-summarization
model-index:
- name: mbert2mbert-arabic-text-summarization-finetuned-xsum_arabic_abstractive_final_finaln
  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. -->

# mbert2mbert-arabic-text-summarization-finetuned-xsum_arabic_abstractive_final_finaln

This model is a fine-tuned version of [malmarjeh/mbert2mbert-arabic-text-summarization](https://huggingface.co/malmarjeh/mbert2mbert-arabic-text-summarization) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2826
- Rouge1: 0.0119
- Rouge2: 0.0
- Rougel: 0.0119
- Rougelsum: 0.0119
- Gen Len: 41.8856

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.5104        | 1.0   | 7915  | 2.3684          | 0.0    | 0.0    | 0.0    | 0.0       | 41.8314 |
| 2.2222        | 2.0   | 15830 | 2.2826          | 0.0119 | 0.0    | 0.0119 | 0.0119    | 41.8856 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1