---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- un_multi
metrics:
- bleu
model-index:
- name: opus-mt-en-ar-evaluated-en-to-ar-4000instances-un_multi-leaningRate2e-05-batchSize8-11-action-1
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: un_multi
      type: un_multi
      args: ar-en
    metrics:
    - name: Bleu
      type: bleu
      value: 51.7715
---

<!-- 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-un_multi-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 un_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1850
- Bleu: 51.7715
- Meteor: 0.5164
- Gen Len: 25.5612

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
| 0.6999        | 0.25  | 100  | 0.1959          | 50.1492 | 0.508  | 25.2788 |
| 0.1994        | 0.5   | 200  | 0.1931          | 51.003  | 0.513  | 25.4038 |
| 0.1863        | 0.75  | 300  | 0.1864          | 51.3268 | 0.5145 | 25.1675 |
| 0.1826        | 1.0   | 400  | 0.1841          | 51.2507 | 0.513  | 25.2388 |
| 0.1494        | 1.25  | 500  | 0.1840          | 51.4291 | 0.5159 | 25.4225 |
| 0.1483        | 1.5   | 600  | 0.1839          | 51.2645 | 0.5126 | 25.395  |
| 0.1547        | 1.75  | 700  | 0.1837          | 51.7589 | 0.5157 | 25.48   |
| 0.1487        | 2.0   | 800  | 0.1845          | 51.896  | 0.5177 | 25.3988 |
| 0.1235        | 2.25  | 900  | 0.1852          | 52.0583 | 0.5177 | 25.5212 |
| 0.1164        | 2.5   | 1000 | 0.1850          | 51.7715 | 0.5164 | 25.5612 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1