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---
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
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