---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: helsinki-opus-de-en-fine-tuned-wmt16-finetuned-src-to-trg
  results: []
---

<!-- 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. -->

# 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: 0.9684
- Rouge1: 63.4933
- Rouge2: 31.4582
- Rougel: 60.1644
- Rougelsum: 60.1675
- Gen Len: 23.6657
- Bleu-1: 63.2918
- Bleu-2: 44.1514
- Bleu-3: 31.6161
- Bleu-4: 23.2357
- Meteor: 0.5330

## 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: 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len | Bleu-1  | Bleu-2  | Bleu-3  | Bleu-4  | Meteor |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:-------:|:------:|
| 0.7348        | 1.0   | 1189 | 0.9407          | 61.8229 | 29.2612 | 58.4443 | 58.4242   | 25.6717 | 60.1910 | 40.8083 | 28.4530 | 20.4451 | 0.5069 |
| 0.7794        | 2.0   | 2378 | 0.8899          | 62.6968 | 30.8608 | 59.6691 | 59.7023   | 22.2829 | 60.8908 | 42.4421 | 30.4327 | 22.2917 | 0.5153 |
| 0.6464        | 3.0   | 3567 | 0.8960          | 63.399  | 31.2227 | 60.0505 | 60.0958   | 24.0847 | 62.5712 | 43.4595 | 30.9384 | 22.7195 | 0.5269 |
| 0.5419        | 4.0   | 4756 | 0.9126          | 63.4944 | 30.9818 | 60.1074 | 60.095    | 22.9259 | 61.9100 | 42.9890 | 30.6511 | 22.4916 | 0.5242 |
| 0.4666        | 5.0   | 5945 | 0.9249          | 63.9576 | 31.6972 | 60.6369 | 60.6662   | 23.708  | 63.1527 | 44.3529 | 32.3818 | 24.4188 | 0.5339 |
| 0.4009        | 6.0   | 7134 | 0.9534          | 63.6549 | 32.2835 | 60.3324 | 60.344    | 23.4327 | 63.0061 | 44.5392 | 32.1776 | 23.9321 | 0.5342 |
| 0.3523        | 7.0   | 8323 | 0.9684          | 63.4933 | 31.4582 | 60.1644 | 60.1675   | 23.6657 | 63.2918 | 44.1514 | 31.6161 | 23.2357 | 0.5330 |


### Framework versions

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