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README.md
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---
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license: mit
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base_model: beomi/KcELECTRA-base-v2022
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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model-index:
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- name: KcELECTRA-base-v2022-KEmoFact-EFE-0927
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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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# KcELECTRA-base-v2022-KEmoFact-EFE-0927
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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: 0.5879
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- Precision: 0.4052
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- Recall: 0.4497
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- F1: 0.4263
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- Ov Accuracy: 0.8253
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- Jaccard: 0.7374
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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: 5e-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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- 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 | Precision | Recall | F1 | Ov Accuracy | Jaccard |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:-----------:|:-------:|
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| No log | 1.0 | 414 | 0.4141 | 0.3382 | 0.3897 | 0.3622 | 0.8209 | 0.6966 |
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| 0.4519 | 2.0 | 828 | 0.4230 | 0.3456 | 0.3988 | 0.3703 | 0.8211 | 0.7086 |
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| 0.302 | 3.0 | 1242 | 0.4758 | 0.3660 | 0.4208 | 0.3915 | 0.8204 | 0.7164 |
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| 0.2037 | 4.0 | 1656 | 0.5589 | 0.3649 | 0.4083 | 0.3854 | 0.8193 | 0.7084 |
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| 0.1394 | 5.0 | 2070 | 0.6199 | 0.3533 | 0.4089 | 0.3791 | 0.8148 | 0.7064 |
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### Framework versions
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- Transformers 4.33.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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