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

# resultsara_bertscore

This model is a fine-tuned version of [moussaKam/AraBART](https://huggingface.co/moussaKam/AraBART) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5783

## 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: 128
- eval_batch_size: 128
- 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: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7346        | 0.4263 | 500  | 0.5939          |
| 0.7367        | 0.8525 | 1000 | 0.5851          |
| 0.7042        | 1.2788 | 1500 | 0.5825          |
| 0.6854        | 1.7050 | 2000 | 0.5783          |
| 0.6767        | 2.1313 | 2500 | 0.5775          |
| 0.6561        | 2.5575 | 3000 | 0.5758          |
| 0.6562        | 2.9838 | 3500 | 0.5748          |
| 0.6457        | 3.4101 | 4000 | 0.5774          |
| 0.6519        | 3.8363 | 4500 | 0.5755          |
| 0.6396        | 4.2626 | 5000 | 0.5774          |
| 0.626         | 4.6888 | 5500 | 0.5773          |
| 0.6201        | 5.1151 | 6000 | 0.5789          |
| 0.605         | 5.5413 | 6500 | 0.5776          |
| 0.6044        | 5.9676 | 7000 | 0.5770          |
| 0.5899        | 6.3939 | 7500 | 0.5786          |
| 0.5917        | 6.8201 | 8000 | 0.5779          |
| 0.5913        | 7.2464 | 8500 | 0.5783          |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1