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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: korean_sentiment_analysis_kcelectra |
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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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# korean_sentiment_analysis_kcelectra |
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This model is a fine-tuned version of [beomi/KcELECTRA-base-v2022](https://huggingface.co/beomi/KcELECTRA-base-v2022) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9718 |
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- Micro f1 score: 70.7183 |
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- Auprc: 68.4562 |
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- Accuracy: 0.7072 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 256 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Micro f1 score | Auprc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:-------:|:--------:| |
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| 1.0543 | 1.0 | 391 | 0.9923 | 65.3061 | 49.6906 | 0.6531 | |
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| 0.8573 | 2.0 | 782 | 0.8229 | 69.9901 | 64.4071 | 0.6999 | |
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| 0.7217 | 3.0 | 1173 | 0.7961 | 71.0600 | 67.4640 | 0.7106 | |
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| 0.6305 | 4.0 | 1564 | 0.8163 | 71.1229 | 68.5191 | 0.7112 | |
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| 0.5294 | 5.0 | 1955 | 0.8205 | 71.0150 | 68.7334 | 0.7102 | |
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| 0.4689 | 6.0 | 2346 | 0.8716 | 71.1679 | 68.7751 | 0.7117 | |
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| 0.433 | 7.0 | 2737 | 0.9086 | 70.9880 | 68.3653 | 0.7099 | |
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| 0.419 | 8.0 | 3128 | 0.9290 | 70.6734 | 68.4606 | 0.7067 | |
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| 0.3766 | 9.0 | 3519 | 0.9619 | 70.6464 | 68.5132 | 0.7065 | |
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| 0.3395 | 10.0 | 3910 | 0.9718 | 70.7183 | 68.4562 | 0.7072 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.6.0 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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