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README.md
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---
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license: apache-2.0
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base_model: monologg/koelectra-base-v3-discriminator
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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: koelectra-base-v3-discriminator-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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# koelectra-base-v3-discriminator-KEmoFact-EFE-0927
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This model is a fine-tuned version of [monologg/koelectra-base-v3-discriminator](https://huggingface.co/monologg/koelectra-base-v3-discriminator) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5635
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- Precision: 0.3754
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- Recall: 0.4417
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- F1: 0.4058
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- Ov Accuracy: 0.8248
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- Jaccard: 0.7349
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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 | 0.4083 | 0.3175 | 0.3909 | 0.3504 | 0.8258 | 0.6953 |
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| 0.4405 | 2.0 | 828 | 0.4039 | 0.3208 | 0.4078 | 0.3591 | 0.8256 | 0.7080 |
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| 0.3005 | 3.0 | 1242 | 0.4682 | 0.3448 | 0.4123 | 0.3755 | 0.8251 | 0.7108 |
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| 0.207 | 4.0 | 1656 | 0.5329 | 0.3451 | 0.4218 | 0.3797 | 0.8207 | 0.7076 |
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| 0.1468 | 5.0 | 2070 | 0.5888 | 0.3456 | 0.4235 | 0.3806 | 0.8182 | 0.7093 |
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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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