---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wmt16
metrics:
- bleu
base_model: Helsinki-NLP/opus-mt-tr-en
model-index:
- name: opus-mt-tr-en-finetuned-en-to-tr
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: wmt16
      type: wmt16
      config: tr-en
      split: train
      args: tr-en
    metrics:
    - type: bleu
      value: 6.471
      name: Bleu
---

<!-- 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-tr-en-finetuned-en-to-tr

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-tr-en](https://huggingface.co/Helsinki-NLP/opus-mt-tr-en) on the wmt16 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9429
- Bleu: 6.471
- Gen Len: 56.1688

## 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: 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
| 1.5266        | 1.0   | 12860 | 2.2526          | 4.5834 | 55.6563 |
| 1.2588        | 2.0   | 25720 | 2.0113          | 5.9203 | 56.3506 |
| 1.1878        | 3.0   | 38580 | 1.9429          | 6.471  | 56.1688 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2