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README.md ADDED
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+ ---
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+ base_model: ys7yoo/nli_klue_roberta_large_ep9
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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_ys7yoo_nli_klue_roberta_large_ep9_ep9
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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_ys7yoo_nli_klue_roberta_large_ep9_ep9
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+
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+ This model is a fine-tuned version of [ys7yoo/nli_klue_roberta_large_ep9](https://huggingface.co/ys7yoo/nli_klue_roberta_large_ep9) on the klue dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3322
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+ - Mse: 0.3322
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+ - Mae: 0.4242
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+ - R2: 0.8479
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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: 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: 9
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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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+ | 1.1881 | 1.0 | 183 | 0.4082 | 0.4082 | 0.4975 | 0.8131 |
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+ | 0.1751 | 2.0 | 366 | 0.4353 | 0.4353 | 0.4964 | 0.8007 |
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+ | 0.1222 | 3.0 | 549 | 0.3238 | 0.3238 | 0.4144 | 0.8517 |
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+ | 0.0899 | 4.0 | 732 | 0.3434 | 0.3434 | 0.4482 | 0.8428 |
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+ | 0.0659 | 5.0 | 915 | 0.3174 | 0.3174 | 0.4191 | 0.8547 |
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+ | 0.0483 | 6.0 | 1098 | 0.3439 | 0.3439 | 0.4422 | 0.8425 |
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+ | 0.0361 | 7.0 | 1281 | 0.3472 | 0.3472 | 0.4402 | 0.8410 |
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+ | 0.0265 | 8.0 | 1464 | 0.3667 | 0.3667 | 0.4426 | 0.8321 |
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+ | 0.0203 | 9.0 | 1647 | 0.3322 | 0.3322 | 0.4242 | 0.8479 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.1
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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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