---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- opus100
metrics:
- bleu
model-index:
- name: opus-mt-en-ar-evaluated-en-to-ar-1000instancesopus-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: 21.3028
---

<!-- 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-1000instancesopus-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: 0.1421
- Bleu: 21.3028
- Meteor: 0.1285
- Gen Len: 9.975

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
| 1.0508        | 1.0   | 100  | 0.1413          | 27.9009 | 0.1416 | 8.85    |
| 0.1253        | 2.0   | 200  | 0.1372          | 23.11   | 0.1345 | 9.855   |
| 0.1017        | 3.0   | 300  | 0.1390          | 21.7885 | 0.1364 | 9.97    |
| 0.0868        | 4.0   | 400  | 0.1378          | 21.3889 | 0.1314 | 9.835   |
| 0.0754        | 5.0   | 500  | 0.1398          | 22.198  | 0.132  | 9.675   |
| 0.0667        | 6.0   | 600  | 0.1396          | 20.8645 | 0.1308 | 10.055  |
| 0.0604        | 7.0   | 700  | 0.1408          | 20.289  | 0.1303 | 10.53   |
| 0.0553        | 8.0   | 800  | 0.1414          | 21.7023 | 0.1293 | 10.005  |
| 0.0518        | 9.0   | 900  | 0.1421          | 21.3028 | 0.1285 | 9.975   |


### Framework versions

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