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---
license: cc-by-4.0
tags:
- generated_from_trainer
datasets:
- wmt16
metrics:
- bleu
model-index:
- name: opus-mt-tc-big-en-tr-finetuned-en-to-tr
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: wmt16
type: wmt16
config: tr-en
split: validation
args: tr-en
metrics:
- name: Bleu
type: bleu
value: 19.8042
---
<!-- 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-tc-big-en-tr-finetuned-en-to-tr
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-tc-big-en-tr](https://huggingface.co/Helsinki-NLP/opus-mt-tc-big-en-tr) on the wmt16 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6132
- Bleu: 19.8042
- Gen Len: 23.0739
## 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: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.9813 | 1.0 | 12860 | 1.6132 | 19.8042 | 23.0739 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
|