End of training

README.md

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+---
+license: cc-by-sa-4.0
+base_model: klue/bert-base
+tags:
+- generated_from_trainer
+datasets:
+- klue
+metrics:
+- f1
+model-index:
+- name: bert-base-finetuned-ynat
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: klue
+      type: klue
+      config: ynat
+      split: validation
+      args: ynat
+    metrics:
+    - name: F1
+      type: f1
+      value: 0.8673393457362918
+---
+
+<!-- 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. -->
+
+# bert-base-finetuned-ynat
+
+This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the klue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3817
+- F1: 0.8673
+
+## 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: 2e-05
+- train_batch_size: 256
+- eval_batch_size: 256
+- seed: 1
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| No log        | 1.0   | 179  | 0.3817          | 0.8673 |
+| No log        | 2.0   | 358  | 0.4065          | 0.8634 |
+| 0.2194        | 3.0   | 537  | 0.4077          | 0.8624 |
+| 0.2194        | 4.0   | 716  | 0.4443          | 0.8584 |
+| 0.2194        | 5.0   | 895  | 0.4795          | 0.8569 |
+| 0.1477        | 6.0   | 1074 | 0.5159          | 0.8570 |
+| 0.1477        | 7.0   | 1253 | 0.5445          | 0.8569 |
+| 0.1477        | 8.0   | 1432 | 0.5711          | 0.8565 |
+| 0.0849        | 9.0   | 1611 | 0.5913          | 0.8542 |
+| 0.0849        | 10.0  | 1790 | 0.5945          | 0.8553 |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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