Model save

README.md

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+---
+base_model: ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep10
+tags:
+- generated_from_trainer
+datasets:
+- klue
+metrics:
+- accuracy
+- f1
+model-index:
+- name: nli_sts_roberta_large_lr1e-05_wd1e-03_ep10_lr1e-05_wd1e-03_ep10_ckpt
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: klue
+      type: klue
+      config: nli
+      split: validation
+      args: nli
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8963333333333333
+    - name: F1
+      type: f1
+      value: 0.8962457758881018
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# nli_sts_roberta_large_lr1e-05_wd1e-03_ep10_lr1e-05_wd1e-03_ep10_ckpt
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.6903
+- Accuracy: 0.8963
+- F1: 0.8962
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.6445        | 1.0   | 391  | 0.4254          | 0.852    | 0.8512 |
+| 0.2943        | 2.0   | 782  | 0.3371          | 0.889    | 0.8886 |
+| 0.1586        | 3.0   | 1173 | 0.3704          | 0.888    | 0.8881 |
+| 0.0921        | 4.0   | 1564 | 0.4429          | 0.892    | 0.8919 |
+| 0.0565        | 5.0   | 1955 | 0.4864          | 0.899    | 0.8989 |
+| 0.0378        | 6.0   | 2346 | 0.5727          | 0.8963   | 0.8962 |
+| 0.0238        | 7.0   | 2737 | 0.6247          | 0.8957   | 0.8955 |
+| 0.016         | 8.0   | 3128 | 0.6578          | 0.8947   | 0.8945 |
+| 0.0101        | 9.0   | 3519 | 0.6780          | 0.8953   | 0.8952 |
+| 0.0067        | 10.0  | 3910 | 0.6903          | 0.8963   | 0.8962 |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.13.0
+- Tokenizers 0.13.3

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