yiyang0101
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yiyang0101/yiyang-test
Browse files- .gitignore +1 -1
- README.md +7 -7
- model.safetensors +1 -1
- train.py +2 -2
- training_args.bin +1 -1
.gitignore
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yiyang-test/
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README.md
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---
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base_model: bert-base-uncased
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library_name: transformers
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license: apache-2.0
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tags:
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- generated_from_trainer
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model-index:
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- name:
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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#
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| No log | 1.0 | 1 | 0.
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| No log | 2.0 | 2 | 0.
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| No log | 3.0 | 3 | 0.
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### Framework versions
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---
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library_name: transformers
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license: apache-2.0
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base_model: bert-base-uncased
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tags:
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- generated_from_trainer
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model-index:
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- name: bert-base-uncased
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# bert-base-uncased
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7692
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## Model description
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| No log | 1.0 | 1 | 0.7881 |
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| No log | 2.0 | 2 | 0.7738 |
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| No log | 3.0 | 3 | 0.7692 |
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### Framework versions
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model.safetensors
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size 437958648
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train.py
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# 학습 설정
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training_args = TrainingArguments(
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output_dir="./
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evaluation_strategy="epoch",
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learning_rate=2e-5,
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per_device_train_batch_size=16,
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trainer.train()
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# 모델 저장
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trainer.save_model("./")
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# 모델 푸시
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trainer.push_to_hub("yiyang0101/yiyang-test")
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# 학습 설정
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training_args = TrainingArguments(
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output_dir="./", # 학습 결과 저장 경로
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evaluation_strategy="epoch",
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learning_rate=2e-5,
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per_device_train_batch_size=16,
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trainer.train()
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# 모델 저장
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# trainer.save_model("./")
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# 모델 푸시
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trainer.push_to_hub("yiyang0101/yiyang-test")
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training_args.bin
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