metadata

tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: bert-base-chinese-david-ner
    results: []

bert-base-chinese-david-ner

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

Loss: 0.2217
Precision: 0.8020
Recall: 0.8379
F1: 0.8196
Accuracy: 0.9471

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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.2487	1.4	500	0.2446	0.8138	0.8138	0.8138	0.9417
0.0668	2.8	1000	0.2217	0.8020	0.8379	0.8196	0.9471

Framework versions

Transformers 4.29.0.dev0
Pytorch 1.10.1+cu113
Datasets 2.11.0
Tokenizers 0.13.3