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README.md ADDED
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+ ---
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+ library_name: transformers
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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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+ model-index:
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+ - name: ynat_model
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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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+ # ynat_model
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+
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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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+ - eval_loss: 2.0522
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+ - eval_accuracy: 0.0917
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+ - eval_precision: 0.0131
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+ - eval_recall: 0.1429
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+ - eval_f1: 0.0240
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+ - eval_runtime: 14.6861
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+ - eval_samples_per_second: 620.111
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+ - eval_steps_per_second: 38.812
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+ - epoch: 1.0
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+ - step: 2855
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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: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 3
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+
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+ ### Framework versions
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+
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+ - Transformers 4.54.1
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 4.0.0
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+ - Tokenizers 0.21.4
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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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+ "torch_dtype": "float32",
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+ "transformers_version": "4.54.1",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 35000
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+ }
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