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--- |
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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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metrics: |
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- pearsonr |
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model-index: |
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- name: roberta-base-finetuned-sts |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: klue |
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type: klue |
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args: sts |
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metrics: |
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- name: Pearsonr |
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type: pearsonr |
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value: 0.956039443806831 |
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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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# roberta-base-finetuned-sts |
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This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on the klue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1999 |
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- Pearsonr: 0.9560 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 32 |
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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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- lr_scheduler_warmup_steps: 200 |
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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Pearsonr | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 329 | 0.2462 | 0.9478 | |
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| 1.2505 | 2.0 | 658 | 0.1671 | 0.9530 | |
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| 1.2505 | 3.0 | 987 | 0.1890 | 0.9525 | |
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| 0.133 | 4.0 | 1316 | 0.2360 | 0.9548 | |
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| 0.0886 | 5.0 | 1645 | 0.2265 | 0.9528 | |
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| 0.0886 | 6.0 | 1974 | 0.2097 | 0.9518 | |
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| 0.0687 | 7.0 | 2303 | 0.2281 | 0.9523 | |
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| 0.0539 | 8.0 | 2632 | 0.2212 | 0.9542 | |
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| 0.0539 | 9.0 | 2961 | 0.1843 | 0.9532 | |
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| 0.045 | 10.0 | 3290 | 0.1999 | 0.9560 | |
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| 0.0378 | 11.0 | 3619 | 0.2357 | 0.9533 | |
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| 0.0378 | 12.0 | 3948 | 0.2134 | 0.9541 | |
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| 0.033 | 13.0 | 4277 | 0.2273 | 0.9540 | |
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| 0.03 | 14.0 | 4606 | 0.2148 | 0.9533 | |
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| 0.03 | 15.0 | 4935 | 0.2207 | 0.9534 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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