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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- klue |
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metrics: |
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- accuracy |
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model-index: |
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- name: kcbert-base-finetuned |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: klue |
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type: klue |
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args: ynat |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8329856154606347 |
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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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# kcbert-base-finetuned |
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This model is a fine-tuned version of [beomi/kcbert-base](https://huggingface.co/beomi/kcbert-base) on the klue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7393 |
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- Accuracy: 0.8330 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 0.4612 | 1.0 | 2855 | 0.5216 | 0.8143 | |
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| 0.3061 | 2.0 | 5710 | 0.5130 | 0.8248 | |
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| 0.2129 | 3.0 | 8565 | 0.6062 | 0.8257 | |
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| 0.1337 | 4.0 | 11420 | 0.7393 | 0.8330 | |
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| 0.0653 | 5.0 | 14275 | 0.8651 | 0.8302 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.14.0 |
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- Tokenizers 0.10.3 |
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