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---
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
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