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oz1115/ko_bad_content_trainer

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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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+ model-index:
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+ - name: hate
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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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+ # hate
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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 the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3904
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+ - Accuracy: 0.8278
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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: 2e-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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+ - num_epochs: 0.2
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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 |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.4578 | 0.2002 | 734 | 0.3904 | 0.8278 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ {
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+ "_name_or_path": "beomi/KcELECTRA-base",
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+ "architectures": [
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+ "ElectraForSequenceClassification"
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+ ],
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+ "hidden_act": "gelu",
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "summary_activation": "gelu",
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+ "summary_type": "first",
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+ "summary_use_proj": true,
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+ "tokenizer_class": "PreTrainedTokenizerFast",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.42.4",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30000
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+ }
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