Update README.md

README.md

@@ -6,26 +6,32 @@ tags:
 model-index:
 - name: opus-mt-ko-en-Korean_Parallel_Corpora
   results: []
+datasets:
+- Moo/korean-parallel-corpora
+language:
+- ko
+- en
+metrics:
+- bleu
+- rouge
+pipeline_tag: translation
 ---
 
-<!-- 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. -->
-
 # opus-mt-ko-en-Korean_Parallel_Corpora
 
-This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ko-en](https://huggingface.co/Helsinki-NLP/opus-mt-ko-en) on the None dataset.
+This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ko-en](https://huggingface.co/Helsinki-NLP/opus-mt-ko-en).
 
-## Model description
+### Model description
 
-More information needed
+For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Machine%20Translation/Korean%20to%20English%20(Korean%20Parallel%20Corpora)/Korean_Parallel_Corpora_OPUS_Translation_Project.ipynb
 
-## Intended uses & limitations
+### Intended uses & limitations
 
-More information needed
+This model is intended to demonstrate my ability to solve a complex problem using technology.
 
-## Training and evaluation data
+### Training and evaluation data
 
-More information needed
+Dataset Source: https://huggingface.co/datasets/Moo/korean-parallel-corpora
 
 ## Training procedure
 
@@ -44,11 +50,19 @@ The following hyperparameters were used during training:
 
 ### Training results
 
+- eval_loss: 2.6620
+- eval_bleu: 14.3395
+- eval_rouge
+  - rouge1: 0.4391
+  - rouge2: 0.2022
+  - rougeL: 0.3671
+  - rougeLsum: 0.3671
 
+* 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
+- Tokenizers 0.13.3