albert-tiny-chinese-david-ner

This model is a fine-tuned version of ckiplab/albert-tiny-chinese-ws on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.3415
• Precision: 0.6062
• Recall: 0.6690
• F1: 0.6361
• Accuracy: 0.9055

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
0.1796	1.4	500	0.3368	0.6201	0.6586	0.6388	0.9046
0.1374	2.8	1000	0.3415	0.6062	0.6690	0.6361	0.9055

Framework versions

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