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README.md
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---
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license: cc-by-sa-4.0
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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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- pearsonr
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model-index:
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- name: bert-base-finetuned-sts
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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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config: sts
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split: train
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args: sts
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metrics:
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- name: Pearsonr
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type: pearsonr
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value: 0.9116408161709073
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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-finetuned-sts
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This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the klue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3951
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- Pearsonr: 0.9116
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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: 4
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- eval_batch_size: 4
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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: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Pearsonr |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 0.2345 | 1.0 | 2917 | 0.7037 | 0.8757 |
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| 0.1491 | 2.0 | 5834 | 0.4869 | 0.8846 |
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| 0.097 | 3.0 | 8751 | 0.4023 | 0.9041 |
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| 0.0735 | 4.0 | 11668 | 0.3960 | 0.9073 |
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| 0.0644 | 5.0 | 14585 | 0.4838 | 0.8989 |
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| 0.0446 | 6.0 | 17502 | 0.3990 | 0.9078 |
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| 0.0355 | 7.0 | 20419 | 0.3951 | 0.9116 |
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| 0.0277 | 8.0 | 23336 | 0.4284 | 0.9053 |
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| 0.0239 | 9.0 | 26253 | 0.4166 | 0.9073 |
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| 0.0205 | 10.0 | 29170 | 0.4234 | 0.9062 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.0
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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