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--- |
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base_model: ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep10 |
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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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- accuracy |
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- f1 |
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model-index: |
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- name: nli_sts_roberta_large_lr1e-05_wd1e-03_ep10_lr1e-05_wd1e-03_ep10_ckpt |
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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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config: nli |
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split: validation |
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args: nli |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8963333333333333 |
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- name: F1 |
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type: f1 |
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value: 0.8962457758881018 |
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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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# nli_sts_roberta_large_lr1e-05_wd1e-03_ep10_lr1e-05_wd1e-03_ep10_ckpt |
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This model is a fine-tuned version of [ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep10](https://huggingface.co/ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep10) on the klue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6903 |
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- Accuracy: 0.8963 |
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- F1: 0.8962 |
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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: 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.6445 | 1.0 | 391 | 0.4254 | 0.852 | 0.8512 | |
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| 0.2943 | 2.0 | 782 | 0.3371 | 0.889 | 0.8886 | |
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| 0.1586 | 3.0 | 1173 | 0.3704 | 0.888 | 0.8881 | |
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| 0.0921 | 4.0 | 1564 | 0.4429 | 0.892 | 0.8919 | |
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| 0.0565 | 5.0 | 1955 | 0.4864 | 0.899 | 0.8989 | |
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| 0.0378 | 6.0 | 2346 | 0.5727 | 0.8963 | 0.8962 | |
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| 0.0238 | 7.0 | 2737 | 0.6247 | 0.8957 | 0.8955 | |
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| 0.016 | 8.0 | 3128 | 0.6578 | 0.8947 | 0.8945 | |
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| 0.0101 | 9.0 | 3519 | 0.6780 | 0.8953 | 0.8952 | |
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| 0.0067 | 10.0 | 3910 | 0.6903 | 0.8963 | 0.8962 | |
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### Framework versions |
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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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