qa_kor_math

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qa_kor_math

This model is a fine-tuned version of gogamza/kobart-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.3294

Model description

한국어 수학 문제를 입력하면, 문제 유형과 문제 유형에 대한 설명, 풀이(코드), 정답이 출력되도록 fine tuning 했습니다.</br> 문제 유형 종류로는 산술연산, 순서정하기, 조합하기, 수 찾기, 크기 비교, 도형이 있습니다.</br> 아직 원인은 잘 모르겠지만, 정확도가 높지는 않아보입니다..</br>

Intended uses & limitations

Training and evaluation data

TUNiB.ai에서 github에 공개한 train 데이터 셋으로 학습하였습니다.</br>

Training procedure

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 400
• num_epochs: 20

Training results

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2