Update README.md

README.md

@@ -12,44 +12,9 @@ euneeei/hw-midm-7B-nsmc
 ### Training Data
 
 <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-한국어로 된 네이버 영화 리뷰 데이터셋입니다.
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-training_args: TrainingArguments = field(
-        default_factory=lambda: TrainingArguments(
-            output_dir="./results",
-            max_steps=500,
-            logging_steps=20,
-            # save_steps=10,
-            per_device_train_batch_size=1,
-            per_device_eval_batch_size=1,
-            gradient_accumulation_steps=2,
-            gradient_checkpointing=False,
-            group_by_length=False,
-            # learning_rate=1e-4,
-            learning_rate = 2e-4,
-            lr_scheduler_type="cosine",
-            warmup_steps=100,
-            warmup_ratio=0.03,
-            max_grad_norm=0.3,
-            weight_decay=0.05,
-            save_total_limit=20,
-            save_strategy="epoch",
-            num_train_epochs=1,
-            optim="paged_adamw_32bit",
-            fp16=True,
-            remove_unused_columns=False,
-            report_to="wandb",
-        )
-  
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+- 한국어로 된 네이버 영화 리뷰 데이터셋입니다.
+
 
-[More Information Needed]
 
 ## Evaluation
 
@@ -79,22 +44,23 @@ training_args: TrainingArguments = field(
 <!-- These are the evaluation metrics being used, ideally with a description of why. -->
 
 
-precision	recall	f1-score	support
-negative	0.87	0.95	091	492
-positive	0.94	0.87	0.90	508
-accuracy			0.91	1000
-macro avg	0.91	0.91	0.91	1000
-weighted avg	0.91	0.91	0.91	1000
+|     | precision | recall | f1-score | support|
+|----|----|----|-------|------|
+negative| 0.87 | 0.95 | 091 | 492
+positive | 0.94 | 0.87 | 0.90 | 508
+accuracy | | | 0.91 | 1000
+macro avg | 0.91 | 0.91 | 0.91 | 1000
+weighted avg | 0.91 | 0.91 | 0.91 | 1000
 
-confusion metrics
+- ### confusion metrics
 
-[[ 466, 26 ]
-[68, 440]]
+### [[ 466, 26 ]
+### [68, 440]]
 
 [More Information Needed]
 
 ### Results
-정확도 0.51 -> 0.91로 높아졌습니다
+- ###정확도 0.51 -> 0.91로 높아졌습니다
 [More Information Needed]