---
license: mit
tags:
- translation
- generated_from_trainer
datasets:
- tatoeba
metrics:
- bleu
model-index:
- name: ft-tatoeba-ar-en
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: tatoeba
      type: tatoeba
      args: ar-en
    metrics:
    - name: Bleu
      type: bleu
      value: 49.84455855787226
      
widget:
- text: "كريستيانو رونالدو يلعب مع نادي يوفنتوس"
  example_title: "Sentence 1"
- text: "تخرج أحمد من الجامعة الأمريكية في الشارقة الشهر الماضي"
  example_title: "Sentence 2"
- text: "لا يزال ديبالا يلعب لفريق يوفنتوس"
  example_title: "Sentence 3"
- text: "شو عملتوا امس ؟"
  example_title: "Sentence 4"
---


<!-- 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. -->

# ft-tatoeba-ar-en

This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the tatoeba dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7431
- Bleu: 49.8446

## 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: 3
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6