---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- un_multi
metrics:
- bleu
model-index:
- name: opus-mt-en-ar-evaluated-en-to-ar-1000instances-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: 64.0048
---

<!-- 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-1000instances-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: 0.1294
- Bleu: 64.0048
- Meteor: 0.4903
- Gen Len: 21.85

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
| 0.0489        | 1.0   | 100  | 0.1287          | 63.7573 | 0.4877 | 21.79   |
| 0.0447        | 2.0   | 200  | 0.1293          | 63.8776 | 0.49   | 21.875  |
| 0.0442        | 3.0   | 300  | 0.1294          | 64.0048 | 0.4903 | 21.85   |
| 0.0433        | 4.0   | 400  | 0.1294          | 64.0048 | 0.4903 | 21.85   |
| 0.0429        | 5.0   | 500  | 0.1294          | 64.0048 | 0.4903 | 21.85   |
| 0.0435        | 6.0   | 600  | 0.1294          | 64.0048 | 0.4903 | 21.85   |
| 0.0429        | 7.0   | 700  | 0.1294          | 64.0048 | 0.4903 | 21.85   |
| 0.0426        | 8.0   | 800  | 0.1294          | 64.0048 | 0.4903 | 21.85   |


### Framework versions

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