Update: 최종 완료 모델에 대한 README 확정

README.md

@@ -20,25 +20,25 @@ model-index:
       name: text2text-generation             # Optional. Example: Speech Recognition
     metrics:
       - type: bleu         # Required. Example: wer. Use metric id from https://hf.co/metrics
-        value: 0.9529006548919251       # Required. Example: 20.90
+        value: 0.958234790096092       # Required. Example: 20.90
         name: eval_bleu         # Optional. Example: Test WER
-        verified: true              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
+        verified: false              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
       - type: rouge1         # Required. Example: wer. Use metric id from https://hf.co/metrics
-        value: 0.9693520563208838       # Required. Example: 20.90
+        value: 0.9735361877162854       # Required. Example: 20.90
         name: eval_rouge1         # Optional. Example: Test WER
-        verified: true              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
+        verified: false              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
       - type: rouge2         # Required. Example: wer. Use metric id from https://hf.co/metrics
-        value: 0.9444220599246154       # Required. Example: 20.90
+        value: 0.9493975212378124       # Required. Example: 20.90
         name: eval_rouge2       # Optional. Example: Test WER
-        verified: true              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
+        verified: false              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
       - type: rougeL         # Required. Example: wer. Use metric id from https://hf.co/metrics
-        value: 0.9692485601662657       # Required. Example: 20.90
+        value: 0.9734558938864928       # Required. Example: 20.90
         name: eval_rougeL        # Optional. Example: Test WER
-        verified: true              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
+        verified: false              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
       - type: rougeLsum         # Required. Example: wer. Use metric id from https://hf.co/metrics
-        value: 0.9692422603343052       # Required. Example: 20.90
+        value: 0.9734350757552404       # Required. Example: 20.90
         name: eval_rougeLsum        # Optional. Example: Test WER
-        verified: true              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
+        verified: false              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
 ---
 
 # ko-TextNumbarT(TNT Model🧨): Try Korean Reading To Number(한글을 숫자로 바꾸는 모델)
@@ -81,7 +81,8 @@ Want see more detail follow this URL [KoGPT_num_converter](https://github.com/dd
 
 ## Evaluation
 Just using `evaluate-metric/bleu` and `evaluate-metric/rouge` in huggingface `evaluate` library <br />
-[Training wanDB URL](https://wandb.ai/bart_tadev/BartForConditionalGeneration/runs/1chrc03q?workspace=user-bart_tadev)
+[Training wanDB URL](https://wandb.ai/bart_tadev/BartForConditionalGeneration/runs/14hyusvf?workspace=user-bart_tadev)
+
 ## How to Get Started With the Model
 ```python
 from transformers.pipelines import Text2TextGenerationPipeline