README.md

metadata

tags:
  - generated_from_trainer
datasets:
  - peoples_daily_ner
metrics:
  - f1
model-index:
  - name: finetuned-bert-chinese-base
    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: F1
            type: f1
            value: 0.957080981756136

finetuned-bert-chinese-base

This model is a fine-tuned version of bert-base-chinese on the peoples_daily_ner dataset. It achieves the following results on the evaluation set:

• Loss: 0.0185
• F1: 0.9571

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: 5e-05
• train_batch_size: 12
• eval_batch_size: 12
• 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	F1
0.0494	1.0	1739	0.0250	0.9283
0.0146	2.0	3478	0.0202	0.9505
0.0051	3.0	5217	0.0185	0.9571

Framework versions

• Transformers 4.31.0.dev0
• Pytorch 2.0.0
• Datasets 2.1.0
• Tokenizers 0.13.3