update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- conll2003
+metrics:
+- precision
+- recall
+- f1
+model-index:
+- name: roberta-base-finetuned-ner-kmeans
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2003
+      type: conll2003
+      args: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.955868544600939
+    - name: Recall
+      type: recall
+      value: 0.9614658103513412
+    - name: F1
+      type: f1
+      value: 0.9586590074394953
+---
+
+<!-- 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. -->
+
+# roberta-base-finetuned-ner-kmeans
+
+This model is a fine-tuned version of [ArBert/roberta-base-finetuned-ner](https://huggingface.co/ArBert/roberta-base-finetuned-ner) on the conll2003 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0592
+- Precision: 0.9559
+- Recall: 0.9615
+- F1: 0.9587
+
+## 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: 16
+- eval_batch_size: 16
+- 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     |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
+| 0.0248        | 1.0   | 878  | 0.0609          | 0.9507    | 0.9561 | 0.9534 |
+| 0.0163        | 2.0   | 1756 | 0.0640          | 0.9515    | 0.9578 | 0.9546 |
+| 0.0089        | 3.0   | 2634 | 0.0592          | 0.9559    | 0.9615 | 0.9587 |
+
+
+### Framework versions
+
+- Transformers 4.16.2
+- Pytorch 1.10.0+cu111
+- Datasets 1.18.3
+- Tokenizers 0.11.0