update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- peoples_daily_ner
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: ner_peoples_daily
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: peoples_daily_ner
+      type: peoples_daily_ner
+      config: peoples_daily_ner
+      split: train
+      args: peoples_daily_ner
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9205354599829109
+    - name: Recall
+      type: recall
+      value: 0.9365401332946972
+    - name: F1
+      type: f1
+      value: 0.9284688307957485
+    - name: Accuracy
+      type: accuracy
+      value: 0.9929549534505072
+---
+
+<!-- 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. -->
+
+# ner_peoples_daily
+
+This model is a fine-tuned version of [hfl/rbt6](https://huggingface.co/hfl/rbt6) on the peoples_daily_ner dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0249
+- Precision: 0.9205
+- Recall: 0.9365
+- F1: 0.9285
+- Accuracy: 0.9930
+
+## 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: 128
+- eval_batch_size: 128
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.3154        | 1.0   | 164  | 0.0410          | 0.8258    | 0.8684 | 0.8466 | 0.9868   |
+| 0.0394        | 2.0   | 328  | 0.0287          | 0.8842    | 0.9070 | 0.8954 | 0.9905   |
+| 0.0293        | 3.0   | 492  | 0.0264          | 0.8978    | 0.9168 | 0.9072 | 0.9916   |
+| 0.02          | 4.0   | 656  | 0.0254          | 0.9149    | 0.9226 | 0.9188 | 0.9923   |
+| 0.016         | 5.0   | 820  | 0.0250          | 0.9167    | 0.9281 | 0.9224 | 0.9927   |
+| 0.0124        | 6.0   | 984  | 0.0252          | 0.9114    | 0.9328 | 0.9220 | 0.9928   |
+| 0.0108        | 7.0   | 1148 | 0.0249          | 0.9169    | 0.9339 | 0.9254 | 0.9928   |
+| 0.0097        | 8.0   | 1312 | 0.0249          | 0.9205    | 0.9365 | 0.9285 | 0.9930   |
+
+
+### Framework versions
+
+- Transformers 4.23.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.5.2
+- Tokenizers 0.13.1