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--- |
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tags: |
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- generated_from_trainer |
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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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datasets: |
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- gyr66/privacy_detection |
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language: |
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- zh |
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model-index: |
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- name: RoBERTa-ext-large-crf-chinese-finetuned-ner |
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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: 0.6813 |
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- name: Recall |
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type: recall |
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value: 0.7573 |
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- name: F1 |
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type: f1 |
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value: 0.7173 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9639 |
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--- |
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# RoBERTa-ext-large-crf-chinese-finetuned-ner |
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This model is a fine-tuned version of [chinese-roberta-wwm-ext-large](https://huggingface.co/hfl/chinese-roberta-wwm-ext-large) on the [gyr66/privacy_detection](https://huggingface.co/datasets/gyr66/privacy_detection) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7186 |
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- Precision: 0.6813 |
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- Recall: 0.7573 |
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- F1: 0.7173 |
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- Accuracy: 0.9639 |
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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: 4 |
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- eval_batch_size: 8 |
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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: 10 |
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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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| 0.0197 | 1.0 | 503 | 0.6375 | 0.6663 | 0.7314 | 0.6973 | 0.9621 | |
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| 0.0251 | 2.0 | 1006 | 0.6048 | 0.6494 | 0.7435 | 0.6933 | 0.9611 | |
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| 0.0176 | 3.0 | 1509 | 0.6196 | 0.6669 | 0.7389 | 0.7011 | 0.9618 | |
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| 0.0116 | 4.0 | 2012 | 0.6361 | 0.6511 | 0.7560 | 0.6997 | 0.9624 | |
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| 0.0082 | 5.0 | 2515 | 0.6682 | 0.6746 | 0.7387 | 0.7052 | 0.9622 | |
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| 0.0067 | 6.0 | 3018 | 0.6587 | 0.6715 | 0.7409 | 0.7045 | 0.9635 | |
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| 0.0046 | 7.0 | 3521 | 0.6846 | 0.6770 | 0.7613 | 0.7167 | 0.9636 | |
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| 0.0019 | 8.0 | 4024 | 0.7081 | 0.6766 | 0.7510 | 0.7118 | 0.9630 | |
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| 0.0014 | 9.0 | 4527 | 0.7064 | 0.6812 | 0.7553 | 0.7163 | 0.9641 | |
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| 0.001 | 10.0 | 5030 | 0.7186 | 0.6813 | 0.7573 | 0.7173 | 0.9639 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
