---
library_name: transformers
license: apache-2.0
base_model: moussaKam/AraBART
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_summrize1_model
  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. -->

# my_summrize1_model

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: 0.4576
- Rouge1: 0.0134
- Rouge2: 0.005
- Rougel: 0.0129
- Rougelsum: 0.0133
- Gen Len: 20.0

## 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 50   | 0.5512          | 0.008  | 0.0067 | 0.008  | 0.008     | 18.98   |
| No log        | 2.0   | 100  | 0.4914          | 0.0147 | 0.0117 | 0.0158 | 0.0147    | 20.0    |
| No log        | 3.0   | 150  | 0.4659          | 0.0211 | 0.0117 | 0.021  | 0.0209    | 20.0    |
| No log        | 4.0   | 200  | 0.4576          | 0.0134 | 0.005  | 0.0129 | 0.0133    | 20.0    |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0