update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- peoples_daily_ner
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-ner-chinese-people-daily
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: peoples_daily_ner
+      type: peoples_daily_ner
+      config: peoples_daily_ner
+      split: validation
+      args: peoples_daily_ner
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8608247422680413
+    - name: Recall
+      type: recall
+      value: 0.8608247422680413
+    - name: F1
+      type: f1
+      value: 0.8608247422680413
+    - name: Accuracy
+      type: accuracy
+      value: 0.9852778800147222
+---
+
+<!-- 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-chinese-people-daily
+
+This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on the peoples_daily_ner dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0604
+- Precision: 0.8608
+- Recall: 0.8608
+- F1: 0.8608
+- Accuracy: 0.9853
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 131  | 0.0753          | 0.6955    | 0.7887 | 0.7391 | 0.9764   |
+| No log        | 2.0   | 262  | 0.0588          | 0.7971    | 0.8505 | 0.8229 | 0.9840   |
+| No log        | 3.0   | 393  | 0.0604          | 0.8608    | 0.8608 | 0.8608 | 0.9853   |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.1
+- Datasets 2.12.0
+- Tokenizers 0.13.3