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README.md
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model-index:
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- name: opus-mt-zh-en-Chinese_to_English
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# opus-mt-zh-en-Chinese_to_English
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-zh-en](https://huggingface.co/Helsinki-NLP/opus-mt-zh-en)
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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## Training procedure
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### Training results
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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model-index:
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- name: opus-mt-zh-en-Chinese_to_English
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results: []
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datasets:
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- GEM/wiki_lingua
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language:
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- en
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- zh
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metrics:
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- bleu
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- rouge
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pipeline_tag: translation
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---
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# opus-mt-zh-en-Chinese_to_English
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-zh-en](https://huggingface.co/Helsinki-NLP/opus-mt-zh-en).
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## Model description
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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
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## Intended uses & limitations
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This model is intended to demonstrate my ability to solve a complex problem using technology.
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## Training and evaluation data
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Dataset Source: https://huggingface.co/datasets/GEM/wiki_lingua
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__Chinese Text Length__
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__English Text Length__
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## Training procedure
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### Training results
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| Epoch | Validation Loss | Bleu | Rouge1 | Rouge2 | RougeL | RougeLsum | Avg. Prediction Lengths |
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| 1.0 | 1.0113 | 45.2808 | 0.6201 | 0.4198 | 0.5927 | 0.5927 | 24.5581 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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