update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- ontonotes5
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-ner-ontonotes
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: ontonotes5
+      type: ontonotes5
+      config: ontonotes5
+      split: train
+      args: ontonotes5
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8567258883248731
+    - name: Recall
+      type: recall
+      value: 0.8841595180407308
+    - name: F1
+      type: f1
+      value: 0.8702265476459025
+    - name: Accuracy
+      type: accuracy
+      value: 0.9754933764288157
+---
+
+<!-- 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-finetuned-ner-ontonotes
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the ontonotes5 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1503
+- Precision: 0.8567
+- Recall: 0.8842
+- F1: 0.8702
+- Accuracy: 0.9755
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0842        | 1.0   | 7491  | 0.0950          | 0.8524    | 0.8715 | 0.8618 | 0.9745   |
+| 0.0523        | 2.0   | 14982 | 0.1044          | 0.8449    | 0.8827 | 0.8634 | 0.9744   |
+| 0.036         | 3.0   | 22473 | 0.1118          | 0.8529    | 0.8843 | 0.8683 | 0.9760   |
+| 0.0231        | 4.0   | 29964 | 0.1240          | 0.8589    | 0.8805 | 0.8696 | 0.9752   |
+| 0.0118        | 5.0   | 37455 | 0.1416          | 0.8570    | 0.8804 | 0.8685 | 0.9753   |
+| 0.0077        | 6.0   | 44946 | 0.1503          | 0.8567    | 0.8842 | 0.8702 | 0.9755   |
+
+
+### Framework versions
+
+- Transformers 4.22.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.5.1
+- Tokenizers 0.12.1