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
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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