---
library_name: transformers
base_model: malmarjeh/mbert2mbert-arabic-text-summarization
tags:
- generated_from_trainer
model-index:
- name: resultmbert2mbert
  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. -->

# resultmbert2mbert

This model is a fine-tuned version of [malmarjeh/mbert2mbert-arabic-text-summarization](https://huggingface.co./malmarjeh/mbert2mbert-arabic-text-summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8701

## 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: 32
- 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: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 2.551         | 0.4263 | 500   | 1.0592          |
| 1.1939        | 0.8525 | 1000  | 0.9787          |
| 1.0979        | 1.2788 | 1500  | 0.9425          |
| 1.0436        | 1.7050 | 2000  | 0.9134          |
| 1.0132        | 2.1313 | 2500  | 0.9038          |
| 0.9645        | 2.5575 | 3000  | 0.8905          |
| 0.9608        | 2.9838 | 3500  | 0.8857          |
| 0.9526        | 3.4101 | 4000  | 0.8931          |
| 0.96          | 3.8363 | 4500  | 0.8838          |
| 0.9254        | 4.2626 | 5000  | 0.8804          |
| 0.9023        | 4.6888 | 5500  | 0.8724          |
| 0.884         | 5.1151 | 6000  | 0.8754          |
| 0.8496        | 5.5413 | 6500  | 0.8656          |
| 0.85          | 5.9676 | 7000  | 0.8653          |
| 0.8076        | 6.3939 | 7500  | 0.8668          |
| 0.8119        | 6.8201 | 8000  | 0.8655          |
| 0.7953        | 7.2464 | 8500  | 0.8676          |
| 0.7719        | 7.6726 | 9000  | 0.8656          |
| 0.7657        | 8.0989 | 9500  | 0.8710          |
| 0.7446        | 8.5251 | 10000 | 0.8694          |
| 0.7524        | 8.9514 | 10500 | 0.8658          |
| 0.729         | 9.3777 | 11000 | 0.8699          |
| 0.7338        | 9.8039 | 11500 | 0.8701          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1