Update README.md

README.md

@@ -1,77 +1,13 @@
 ---
+language: ko
 tags:
-- generated_from_trainer
+- bert
+- mrc
 datasets:
 - klue
-metrics:
-- f1
-model-index:
-- name: bert-base-finetuned-ynat
-  results:
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: klue
-      type: klue
-      config: ynat
-      split: train
-      args: ynat
-    metrics:
-    - name: F1
-      type: f1
-      value: 0.871180664370084
+license: cc-by-sa-4.0
 ---
 
-<!-- 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. -->
+# 인프런 강의용 checkpoint
 
-# bert-base-finetuned-ynat
-
-This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the klue dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.3609
-- F1: 0.8712
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 256
-- eval_batch_size: 256
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 5
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:------:|
-| No log        | 1.0   | 179  | 0.3979          | 0.8611 |
-| No log        | 2.0   | 358  | 0.3773          | 0.8669 |
-| 0.3007        | 3.0   | 537  | 0.3609          | 0.8712 |
-| 0.3007        | 4.0   | 716  | 0.3708          | 0.8708 |
-| 0.3007        | 5.0   | 895  | 0.3720          | 0.8697 |
-
-
-### Framework versions
-
-- Transformers 4.21.0
-- Pytorch 1.12.0+cu113
-- Datasets 2.4.0
-- Tokenizers 0.12.1
+KLUE의 YNAT task에 파인튜닝된 모델입니다.