transformers pytorch tensorboard marian text2text-generation generated_from_trainer dataset:wmt16 dataset:autoevaluate/wmt16-sample license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- wmt16
- autoevaluate/wmt16-sample
license: apache-2.0
metrics:
- bleu
tags:
- generated_from_trainer
model-index:
- name: translation
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: wmt16
      type: wmt16
      args: ro-en
    metrics:
    - type: bleu
      value: 28.5866
      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. -->

# translation

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ro](https://huggingface.co/Helsinki-NLP/opus-mt-en-ro) on the wmt16 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3170
- Bleu: 28.5866
- Gen Len: 33.9575

## 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
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.8302        | 0.03  | 1000 | 1.3170          | 28.5866 | 33.9575 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
