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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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- f1
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model-index:
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- name: bert-base-finetuned-ynat
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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: ynat
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split: validation
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args: ynat
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metrics:
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- name: F1
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type: f1
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value: 0.8700870690771503
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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-ynat
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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: 0.3653
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- F1: 0.8701
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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: 256
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- eval_batch_size: 256
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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 | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| No log | 1.0 | 179 | 0.4209 | 0.8587 |
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| No log | 2.0 | 358 | 0.3721 | 0.8677 |
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| 0.3779 | 3.0 | 537 | 0.3607 | 0.8686 |
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| 0.3779 | 4.0 | 716 | 0.3659 | 0.8688 |
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| 0.3779 | 5.0 | 895 | 0.3653 | 0.8701 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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