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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
|