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README.md

@@ -1,62 +1,12 @@
 ---
-library_name: transformers
-license: mit
+pipeline_tag: text-classification
+tags: [encoder, binary-classification, routing, ai-champs]
 base_model: intfloat/multilingual-e5-base
-tags:
-- generated_from_trainer
-metrics:
-- accuracy
-- f1
-model-index:
-- name: ai-champ
-  results: []
 ---
 
-<!-- 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. -->
+# ai-champ: Question → A/B 라우팅 분류기
 
-# ai-champ
-
-This model is a fine-tuned version of [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.5180
-- Accuracy: 0.7567
-- F1: 0.7843
-- Roc Auc: 0.8159
-
-## 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: 3e-06
-- train_batch_size: 64
-- eval_batch_size: 128
-- seed: 42
-- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: linear
-- num_epochs: 3
-- mixed_precision_training: Native AMP
-
-### Training results
-
-
-
-### Framework versions
-
-- Transformers 4.56.1
-- Pytorch 2.2.1
-- Datasets 4.0.0
-- Tokenizers 0.22.0
+- 입력: `question` + `[MODEL] {model_name}`
+- 라벨: score ≥ 4 → **B(1)**, else **A(0)**
+- 학습 데이터: `HAERAE-HUB/ai-champs-train`의 train/test 각각 10% 샘플
+- 테스트 메트릭: {'eval_loss': 0.5179986953735352, 'eval_accuracy': 0.7566917950398776, 'eval_f1': 0.7842681391068488, 'eval_roc_auc': 0.8158790589102392, 'eval_runtime': 19.1572, 'eval_samples_per_second': 955.569, 'eval_steps_per_second': 7.517, 'epoch': 3.0}