update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- klue
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: koelectra-base-v3-discriminator-finetuned-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: klue
+      type: klue
+      args: ner
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.6665182546749777
+    - name: Recall
+      type: recall
+      value: 0.7350073648032546
+    - name: F1
+      type: f1
+      value: 0.6990893625537877
+    - name: Accuracy
+      type: accuracy
+      value: 0.9395764497172635
+---
+
+<!-- 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. -->
+
+# koelectra-base-v3-discriminator-finetuned-ner
+
+This model is a fine-tuned version of [monologg/koelectra-base-v3-discriminator](https://huggingface.co/monologg/koelectra-base-v3-discriminator) on the klue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1957
+- Precision: 0.6665
+- Recall: 0.7350
+- F1: 0.6991
+- Accuracy: 0.9396
+
+## 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: 48
+- eval_batch_size: 48
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 438  | 0.2588          | 0.5701    | 0.6655 | 0.6141 | 0.9212   |
+| 0.4333        | 2.0   | 876  | 0.2060          | 0.6671    | 0.7134 | 0.6895 | 0.9373   |
+| 0.1944        | 3.0   | 1314 | 0.1957          | 0.6665    | 0.7350 | 0.6991 | 0.9396   |
+
+
+### Framework versions
+
+- Transformers 4.11.3
+- Pytorch 1.12.0+cu102
+- Datasets 1.14.0
+- Tokenizers 0.10.3