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--- |
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language: |
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- zh |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- gyr66/privacy_detection |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: RoBERTa-finetuned-privacy-detection |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: gyr66/privacy_detection |
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type: gyr66/privacy_detection |
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config: privacy_detection |
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split: train |
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args: privacy_detection |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.6168845082494108 |
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- name: Recall |
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type: recall |
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value: 0.7248237663645518 |
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- name: F1 |
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type: f1 |
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value: 0.6665123278157193 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9061190926862569 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# RoBERTa-finetuned-privacy-detection |
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This model is a fine-tuned version of [gyr66/RoBERTa-finetuned-privacy-detection](https://huggingface.co/gyr66/RoBERTa-finetuned-privacy-detection) on the gyr66/privacy_detection dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3534 |
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- Precision: 0.6169 |
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- Recall: 0.7248 |
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- F1: 0.6665 |
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- Accuracy: 0.9061 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 56 |
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- eval_batch_size: 56 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.2027 | 1.0 | 36 | 0.3485 | 0.5913 | 0.7273 | 0.6523 | 0.9030 | |
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| 0.1652 | 2.0 | 72 | 0.3534 | 0.6153 | 0.7314 | 0.6684 | 0.9053 | |
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| 0.143 | 3.0 | 108 | 0.3534 | 0.6169 | 0.7248 | 0.6665 | 0.9061 | |
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### Framework versions |
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- Transformers 4.27.3 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.2 |
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