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README.md ADDED
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+ ---
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+ base_model: klue/roberta-large
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - klue
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+ model-index:
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+ - name: sts_roberta_large_lr1e-05_wd1e-03_ep10_ckpt
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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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+ # sts_roberta_large_lr1e-05_wd1e-03_ep10_ckpt
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+
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+ This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on the klue dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3764
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+ - Mse: 0.3764
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+ - Mae: 0.4512
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+ - R2: 0.8277
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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: 1e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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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_ratio: 0.1
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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 | Mse | Mae | R2 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
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+ | 2.3411 | 1.0 | 183 | 1.0407 | 1.0407 | 0.7779 | 0.5234 |
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+ | 0.1725 | 2.0 | 366 | 0.3938 | 0.3938 | 0.4710 | 0.8197 |
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+ | 0.1203 | 3.0 | 549 | 0.3972 | 0.3972 | 0.4594 | 0.8181 |
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+ | 0.093 | 4.0 | 732 | 0.4030 | 0.4030 | 0.4675 | 0.8155 |
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+ | 0.0727 | 5.0 | 915 | 0.4102 | 0.4102 | 0.4690 | 0.8122 |
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+ | 0.0591 | 6.0 | 1098 | 0.3700 | 0.3700 | 0.4470 | 0.8306 |
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+ | 0.0482 | 7.0 | 1281 | 0.3578 | 0.3578 | 0.4403 | 0.8362 |
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+ | 0.0417 | 8.0 | 1464 | 0.4042 | 0.4042 | 0.4696 | 0.8149 |
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+ | 0.037 | 9.0 | 1647 | 0.4151 | 0.4151 | 0.4753 | 0.8099 |
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+ | 0.0337 | 10.0 | 1830 | 0.3764 | 0.3764 | 0.4512 | 0.8277 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.2
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.13.0
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+ - Tokenizers 0.13.3
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