---
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-de-en
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: spark-name-de-to-en
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# German Names to English Translation Model

## Model Overview

This translation model is specifically designed to accurately and fluently translate German names and surnames into English.

## Intended Uses and Limitations

This model is built for Spark IT enterprise looking to automate the translation process of German names and surnames into English.

## Training and Evaluation Data

This model has been trained on a diverse dataset consisting of over 68,493 lines of data, encompassing a wide range of Hindi names and surnames along with their English counterparts. Evaluation data has been carefully selected to ensure reliable and accurate translation performance.

## Training Procedure
- 1 days of training

### Hardware Environment:

- Azure Studio 
- Standard_DS12_v2
- 4 cores, 28GB RAM, 56GB storage
- Data manipulation and training on medium-sized datasets (1-10GB)
- 6 cores
- Loss: 0.4618
- Bleu: 70.7674
- Gen Len: 10.2548


### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 1.0715        | 1.0   | 1600 | 0.9902          | 41.5519 | 5.8328  |
| 0.8185        | 2.0   | 3200 | 0.9547          | 53.8222 | 5.7988  |
| 0.6909        | 3.0   | 4800 | 0.9527          | 54.7846 | 5.8169  |
| 0.6038        | 4.0   | 6400 | 0.9496          | 55.6009 | 5.8406  |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.2+cpu
- Datasets 2.15.0
- Tokenizers 0.15.2