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opus-mt-zh-en-Chinese_to_English

This model is a fine-tuned version of Helsinki-NLP/opus-mt-zh-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/Chinese%20to%20English%20Translation/Chinese_to_English_Translation.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/GEM/wiki_lingua

Chinese Text Length Chinese Text Length

English Text Length English Text Length__

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: 1

Training results

Epoch Validation Loss Bleu Rouge1 Rouge2 RougeL RougeLsum Avg. Prediction Lengths
1.0 1.0113 45.2808 0.6201 0.4198 0.5927 0.5927 24.5581

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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Finetuned from

Dataset used to train DunnBC22/opus-mt-zh-en-Chinese_to_English

Space using DunnBC22/opus-mt-zh-en-Chinese_to_English 1

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