transformers pytorch tensorboard marian text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: helsinki-opus-de-en-fine-tuned-wmt16-finetuned-src-to-trg
  results: []
---

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# helsinki-opus-de-en-fine-tuned-wmt16-finetuned-src-to-trg

This model is a fine-tuned version of [mariav/helsinki-opus-de-en-fine-tuned-wmt16](https://huggingface.co/mariav/helsinki-opus-de-en-fine-tuned-wmt16) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8597
- Rouge1: 64.539
- Rouge2: 32.7634
- Rougel: 61.3523
- Rougelsum: 61.3758
- Gen Len: 23.9561
- Bleu-1: 64.1391
- Bleu-2: 45.1093
- Bleu-3: 32.4697
- Bleu-4: 24.2684
- Meteor: 0.5436

## Model description

This model is a fine-tuned version of mariav/helsinki-opus-de-en-fine-tuned-wmt16 on Phoenix Weather dataset (PHOENIX-2014-T). 


## Intended uses & limitations

The purpose is Neural Machine Translation from German text into German Sign Glosses, which could be used for avatar generation within the Sign Language Production task. 

## Training and evaluation data

Phoenix Weather dataset (PHOENIX-2014-T)

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 5
- eval_batch_size: 5
- seed: 7575
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len | Bleu-1  | Bleu-2  | Bleu-3  | Bleu-4  | Meteor |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:-------:|:------:|
| 1.1513        | 1.0   | 1189 | 0.9604          | 61.8236 | 30.0156 | 58.9651 | 58.9484   | 22.8563 | 58.6480 | 40.5508 | 29.0090 | 21.2884 | 0.4961 |
| 0.9067        | 2.0   | 2378 | 0.8825          | 62.8824 | 30.8604 | 59.9543 | 59.9884   | 22.7564 | 60.5598 | 42.0443 | 29.9532 | 21.8711 | 0.5138 |
| 0.739         | 3.0   | 3567 | 0.8547          | 63.8251 | 31.6294 | 60.7141 | 60.7508   | 24.5219 | 62.6847 | 43.6395 | 31.1174 | 22.8704 | 0.5318 |
| 0.636         | 4.0   | 4756 | 0.8554          | 64.5308 | 32.6897 | 61.347  | 61.3929   | 22.7912 | 63.0309 | 44.4786 | 32.0956 | 23.8647 | 0.5369 |
| 0.5745        | 5.0   | 5945 | 0.8597          | 64.539  | 32.7634 | 61.3523 | 61.3758   | 23.9561 | 64.1391 | 45.1093 | 32.4697 | 24.2684 | 0.5436 |


### Framework versions

- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
