---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- un_multi
metrics:
- bleu
model-index:
- name: opus-mt-en-ar-evaluated-en-to-ar-2000instances-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: 53.0137
---

<!-- 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-2000instances-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: 0.1873
- Bleu: 53.0137
- Meteor: 0.5005
- Gen Len: 25.845

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
| 0.6585        | 0.5   | 100  | 0.2085          | 52.5874 | 0.4969 | 25.485  |
| 0.1802        | 1.0   | 200  | 0.1788          | 52.9434 | 0.4982 | 25.1725 |
| 0.1501        | 1.5   | 300  | 0.1683          | 53.6994 | 0.5033 | 25.625  |
| 0.1454        | 2.0   | 400  | 0.1706          | 53.3946 | 0.5005 | 25.6675 |
| 0.1193        | 2.5   | 500  | 0.1774          | 53.2011 | 0.4982 | 25.58   |
| 0.1194        | 3.0   | 600  | 0.1741          | 53.8651 | 0.5026 | 25.5775 |
| 0.1002        | 3.5   | 700  | 0.1878          | 53.1332 | 0.5005 | 25.8975 |
| 0.0979        | 4.0   | 800  | 0.1881          | 52.5989 | 0.4974 | 25.485  |
| 0.0807        | 4.5   | 900  | 0.1873          | 53.0137 | 0.5005 | 25.845  |


### Framework versions

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