---
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