update model card README.md

README.md

@@ -0,0 +1,67 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-base-uncased-finetuned-ner-kmeans
+  results: []
+---
+
+<!-- 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-uncased-finetuned-ner-kmeans
+
+This model is a fine-tuned version of [ArBert/bert-base-uncased-finetuned-ner](https://huggingface.co/ArBert/bert-base-uncased-finetuned-ner) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1169
+- Precision: 0.9084
+- Recall: 0.9245
+- F1: 0.9164
+- Accuracy: 0.9792
+
+## 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     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.036         | 1.0   | 1123 | 0.1010          | 0.9086    | 0.9117 | 0.9101 | 0.9779   |
+| 0.0214        | 2.0   | 2246 | 0.1094          | 0.9033    | 0.9199 | 0.9115 | 0.9784   |
+| 0.014         | 3.0   | 3369 | 0.1169          | 0.9084    | 0.9245 | 0.9164 | 0.9792   |
+
+
+### Framework versions
+
+- Transformers 4.16.2
+- Pytorch 1.10.0+cu111
+- Datasets 1.18.3
+- Tokenizers 0.11.0