---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- opus100
metrics:
- bleu
model-index:
- name: opus-mt-en-ar-evaluated-en-to-ar-2000instancesopus-leaningRate2e-05-batchSize8-11epoch-3
  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: 26.2629
---

<!-- 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-2000instancesopus-leaningRate2e-05-batchSize8-11epoch-3

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: 0.1959
- Bleu: 26.2629
- Meteor: 0.1703
- Gen Len: 11.0925

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Meteor | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
| 1.0519        | 0.5   | 100  | 0.1985          | 27.3525 | 0.1815 | 11.0725 |
| 0.1947        | 1.0   | 200  | 0.1902          | 26.9728 | 0.1789 | 10.82   |
| 0.1489        | 1.5   | 300  | 0.1910          | 27.7003 | 0.1811 | 10.975  |
| 0.1665        | 2.0   | 400  | 0.1905          | 26.3739 | 0.1772 | 11.1075 |
| 0.1321        | 2.5   | 500  | 0.1926          | 26.752  | 0.1772 | 10.975  |
| 0.1271        | 3.0   | 600  | 0.1927          | 27.3663 | 0.1751 | 10.9725 |
| 0.1105        | 3.5   | 700  | 0.1952          | 27.134  | 0.1738 | 10.9975 |
| 0.109         | 4.0   | 800  | 0.1959          | 26.2629 | 0.1703 | 11.0925 |


### Framework versions

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