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kobigbird-bert-base-finetuned-klue

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+ ---
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: kobigbird-bert-base-finetuned-klue
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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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+ # kobigbird-bert-base-finetuned-klue
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+
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+ This model is a fine-tuned version of [monologg/kobigbird-bert-base](https://huggingface.co/monologg/kobigbird-bert-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.9124
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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: 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: 60
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 5.1951 | 0.69 | 500 | 3.9518 |
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+ | 3.7508 | 1.38 | 1000 | 3.4423 |
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+ | 3.4379 | 2.07 | 1500 | 3.1397 |
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+ | 3.1865 | 2.76 | 2000 | 2.8141 |
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+ | 2.9852 | 3.45 | 2500 | 2.6055 |
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+ | 2.7907 | 4.14 | 3000 | 2.4892 |
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+ | 2.6985 | 4.83 | 3500 | 2.4130 |
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+ | 2.63 | 5.52 | 4000 | 2.3479 |
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+ | 2.5616 | 6.21 | 4500 | 2.3134 |
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+ | 2.4898 | 6.9 | 5000 | 2.2526 |
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+ | 2.4167 | 7.59 | 5500 | 2.2422 |
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+ | 2.3861 | 8.28 | 6000 | 2.2138 |
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+ | 2.3401 | 8.97 | 6500 | 2.1762 |
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+ | 2.292 | 9.66 | 7000 | 2.1417 |
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+ | 2.2705 | 10.34 | 7500 | 2.1148 |
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+ | 2.2139 | 11.03 | 8000 | 2.1357 |
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+ | 2.187 | 11.72 | 8500 | 2.0995 |
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+ | 2.1518 | 12.41 | 9000 | 2.0554 |
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+ | 2.1179 | 13.1 | 9500 | 2.0467 |
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+ | 2.0781 | 13.79 | 10000 | 2.0418 |
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+ | 2.0457 | 14.48 | 10500 | 2.0057 |
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+ | 2.0326 | 15.17 | 11000 | 2.0022 |
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+ | 1.9976 | 15.86 | 11500 | 2.0137 |
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+ | 1.9602 | 16.55 | 12000 | 1.9703 |
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+ | 1.9435 | 17.24 | 12500 | 1.9920 |
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+ | 1.9092 | 17.93 | 13000 | 1.9504 |
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+ | 1.8714 | 18.62 | 13500 | 1.9731 |
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+ | 1.8715 | 19.31 | 14000 | 1.9471 |
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+ | 1.8824 | 20.0 | 14500 | 1.9462 |
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+ | 1.8261 | 20.69 | 15000 | 1.9412 |
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+ | 1.815 | 21.38 | 15500 | 1.9308 |
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+ | 1.7988 | 22.07 | 16000 | 1.9285 |
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+ | 1.7722 | 22.76 | 16500 | 1.9341 |
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+ | 1.7606 | 23.45 | 17000 | 1.9007 |
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+ | 1.7402 | 24.14 | 17500 | 1.9206 |
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+ | 1.7177 | 24.83 | 18000 | 1.9125 |
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+ | 1.7117 | 25.52 | 18500 | 1.9178 |
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+ | 1.6834 | 26.21 | 19000 | 1.9082 |
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+ | 1.6893 | 26.9 | 19500 | 1.9124 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.18.0
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+ - Pytorch 1.11.0.dev20211231+cu113
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+ - Datasets 2.1.0
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+ - Tokenizers 0.12.1