---
base_model: Helsinki-NLP/opus-mt-en-ar
library_name: transformers
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: Finetuning_mt-en-ar_English_Arabic_Translation
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Finetuning_mt-en-ar_English_Arabic_Translation

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ar](https://huggingface.co/Helsinki-NLP/opus-mt-en-ar) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1618

## 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: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.3063        | 1.0   | 2000  | 0.2406          |
| 0.2338        | 2.0   | 4000  | 0.2032          |
| 0.2047        | 3.0   | 6000  | 0.1842          |
| 0.1698        | 4.0   | 8000  | 0.1738          |
| 0.1586        | 5.0   | 10000 | 0.1690          |
| 0.1394        | 6.0   | 12000 | 0.1664          |
| 0.1307        | 7.0   | 14000 | 0.1636          |
| 0.1229        | 8.0   | 16000 | 0.1627          |
| 0.1176        | 9.0   | 18000 | 0.1611          |
| 0.1094        | 10.0  | 20000 | 0.1608          |
| 0.1007        | 11.0  | 22000 | 0.1600          |
| 0.0959        | 12.0  | 24000 | 0.1610          |
| 0.0955        | 13.0  | 26000 | 0.1609          |
| 0.0942        | 14.0  | 28000 | 0.1618          |
| 0.0904        | 15.0  | 30000 | 0.1618          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1