RoBERTa-ext-large-chinese-finetuned-ner
This model is a fine-tuned version of chinese-roberta-wwm-ext-large on the gyr66/privacy_detection dataset. It achieves the following results on the evaluation set:
- Loss: 0.7697
- Precision: 0.7052
- Recall: 0.7606
- F1: 0.7318
- Accuracy: 0.9138
Model description
The model is used for competition: "https://www.datafountain.cn/competitions/472"
Training and evaluation data
The training and evaluation data is from gyr66/privacy_detection dataset.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 28
- eval_batch_size: 28
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
Framework versions
- Transformers 4.27.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.2
- Downloads last month
- 42
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for gyr66/RoBERTa-ext-large-chinese-finetuned-ner
Dataset used to train gyr66/RoBERTa-ext-large-chinese-finetuned-ner
Evaluation results
- Precision on gyr66/privacy_detectionself-reported0.705
- Recall on gyr66/privacy_detectionself-reported0.761
- F1 on gyr66/privacy_detectionself-reported0.732
- Accuracy on gyr66/privacy_detectionself-reported0.914