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: distilbert-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: 0.8535359959297889
+    - name: Recall
+      type: recall
+      value: 0.8788553467356427
+    - name: F1
+      type: f1
+      value: 0.8660106468785288
+    - name: Accuracy
+      type: accuracy
+      value: 0.9749625470373822
+---
+
+<!-- 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. -->
+
+# distilbert-finetuned-ner-ontonotes
+
+This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the ontonotes5 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1448
+- Precision: 0.8535
+- Recall: 0.8789
+- F1: 0.8660
+- Accuracy: 0.9750
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0937        | 1.0   | 7491  | 0.0998          | 0.8367    | 0.8587 | 0.8475 | 0.9731   |
+| 0.0572        | 2.0   | 14982 | 0.1084          | 0.8338    | 0.8759 | 0.8543 | 0.9737   |
+| 0.0403        | 3.0   | 22473 | 0.1145          | 0.8521    | 0.8707 | 0.8613 | 0.9748   |
+| 0.0265        | 4.0   | 29964 | 0.1222          | 0.8535    | 0.8815 | 0.8672 | 0.9752   |
+| 0.0148        | 5.0   | 37455 | 0.1365          | 0.8536    | 0.8770 | 0.8651 | 0.9747   |
+| 0.0111        | 6.0   | 44946 | 0.1448          | 0.8535    | 0.8789 | 0.8660 | 0.9750   |
+
+
+### Framework versions
+
+- Transformers 4.22.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.5.1
+- Tokenizers 0.12.1