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--- |
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base_model: ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep5 |
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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_ep5_lr1e-05_wd1e-03_ep5_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: 0.8986666666666666 |
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- name: F1 |
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type: f1 |
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value: 0.8985280502079203 |
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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_ep5_lr1e-05_wd1e-03_ep5_ckpt |
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This model is a fine-tuned version of [ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep5](https://huggingface.co/ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep5) on the klue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4971 |
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- Accuracy: 0.8987 |
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- F1: 0.8985 |
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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: 5 |
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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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| 0.5471 | 1.0 | 391 | 0.3522 | 0.876 | 0.8756 | |
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| 0.2379 | 2.0 | 782 | 0.3345 | 0.8983 | 0.8981 | |
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| 0.1215 | 3.0 | 1173 | 0.3708 | 0.8997 | 0.8995 | |
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| 0.0661 | 4.0 | 1564 | 0.4734 | 0.896 | 0.8958 | |
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| 0.0407 | 5.0 | 1955 | 0.4971 | 0.8987 | 0.8985 | |
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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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