---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- news_commentary
metrics:
- bleu
model-index:
- name: opus-mt-ar-en-finetuned-ar-to-en
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: news_commentary
      type: news_commentary
      args: ar-en
    metrics:
    - name: Bleu
      type: bleu
      value: 0.0756
---

<!-- 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-ar-en-finetuned-ar-to-en

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ar-en](https://huggingface.co/Helsinki-NLP/opus-mt-ar-en) on the news_commentary dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2173
- Bleu: 0.0756
- Gen Len: 330.32

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 4    | 5.5459          | 0.1405 | 511.0   |
| No log        | 2.0   | 8    | 3.8021          | 0.0206 | 511.0   |
| No log        | 3.0   | 12   | 3.2173          | 0.0756 | 330.32  |


### Framework versions

- Transformers 4.19.4
- Pytorch 1.11.0+cu113
- Datasets 2.3.0
- Tokenizers 0.12.1