---
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