Edit model card

opus-mt-de-en-OPUS_Medical_German_to_English

This model is a fine-tuned version of Helsinki-NLP/opus-mt-de-en.

Model description

For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Machine%20Translation/Medical%20-%20German%20to%20English/OPUS_Medical_German_to_English_OPUS_Translation_Project.ipynb

Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology.

Training and evaluation data

Dataset Source: https://huggingface.co/datasets/ahazeemi/opus-medical-en-de

Histogram of German Input Word Counts

German Word Count of Input Text

Histogram of English Input Word Counts

English Word Count of Input Text

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

  • eval_loss: 0.8723
  • eval_bleu: 53.88120
  • eval_rouge:
    • rouge1: 0.7664
    • rouge2: 0.6284
    • rougeL: 0.7370
    • rougeLsum: 0.7370
  • The training results values are rounded to the nearest ten-thousandth.

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3
Downloads last month
28
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for DunnBC22/opus-mt-de-en-OPUS_Medical_German_to_English

Finetuned
(9)
this model

Dataset used to train DunnBC22/opus-mt-de-en-OPUS_Medical_German_to_English

Collections including DunnBC22/opus-mt-de-en-OPUS_Medical_German_to_English