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Training in progress, epoch 3

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: beomi/KcELECTRA-base
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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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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: 0322_cosmetic3_kcelectra
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+ results: []
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+ ---
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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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+
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+ # 0322_cosmetic3_kcelectra
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+
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+ This model is a fine-tuned version of [beomi/KcELECTRA-base](https://huggingface.co/beomi/KcELECTRA-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3637
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+ - Accuracy: 0.8700
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+ - F1: 0.8703
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+ - Precision: 0.8789
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+ - Recall: 0.8700
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 8
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+ - eval_batch_size: 8
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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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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.4536 | 1.0 | 277 | 0.3556 | 0.8768 | 0.8734 | 0.8873 | 0.8768 |
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+ | 0.2608 | 2.0 | 554 | 0.5060 | 0.8261 | 0.8252 | 0.8415 | 0.8261 |
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+ | 0.1171 | 3.0 | 831 | 0.5406 | 0.8623 | 0.8571 | 0.8768 | 0.8623 |
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+ | 0.1393 | 4.0 | 1108 | 0.5734 | 0.8768 | 0.8752 | 0.8862 | 0.8768 |
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+ | 0.2115 | 5.0 | 1385 | 0.6661 | 0.8913 | 0.8915 | 0.8924 | 0.8913 |
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+ | 0.0939 | 6.0 | 1662 | 0.5506 | 0.9058 | 0.9054 | 0.9057 | 0.9058 |
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+ | 0.1122 | 7.0 | 1939 | 0.6672 | 0.8986 | 0.8985 | 0.8987 | 0.8986 |
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+ | 0.2413 | 8.0 | 2216 | 0.7136 | 0.8949 | 0.8949 | 0.8950 | 0.8949 |
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+ | 0.001 | 9.0 | 2493 | 0.6689 | 0.9058 | 0.9058 | 0.9058 | 0.9058 |
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+ | 0.0013 | 10.0 | 2770 | 0.6764 | 0.9094 | 0.9094 | 0.9094 | 0.9094 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.1
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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