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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- opus100
metrics:
- bleu
model-index:
- name: opus-mt-en-ar-evaluated-en-to-ar-4000instances-opus-leaningRate2e-05-batchSize8-11-action-1
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: opus100
type: opus100
args: ar-en
metrics:
- name: Bleu
type: bleu
value: 26.8232
---
<!-- 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. -->
# opus-mt-en-ar-evaluated-en-to-ar-4000instances-opus-leaningRate2e-05-batchSize8-11-action-1
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 opus100 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1717
- Bleu: 26.8232
- Meteor: 0.172
- Gen Len: 12.1288
## 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: 11
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Meteor | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
| 0.7364 | 0.25 | 100 | 0.1731 | 27.2753 | 0.1729 | 12.0887 |
| 0.2175 | 0.5 | 200 | 0.1731 | 27.2055 | 0.1722 | 11.5675 |
| 0.2193 | 0.75 | 300 | 0.1722 | 27.3277 | 0.1798 | 12.1325 |
| 0.2321 | 1.0 | 400 | 0.1750 | 27.5152 | 0.1762 | 11.925 |
| 0.1915 | 1.25 | 500 | 0.1690 | 27.5043 | 0.1751 | 11.9038 |
| 0.1794 | 1.5 | 600 | 0.1719 | 26.8607 | 0.1713 | 11.8138 |
| 0.1741 | 1.75 | 700 | 0.1725 | 26.974 | 0.1724 | 11.8462 |
| 0.1732 | 2.0 | 800 | 0.1717 | 26.8232 | 0.172 | 12.1288 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
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