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--- |
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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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- peoples_daily_ner |
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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: ner_peoples_daily |
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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: peoples_daily_ner |
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type: peoples_daily_ner |
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config: peoples_daily_ner |
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split: train |
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args: peoples_daily_ner |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.9205354599829109 |
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- name: Recall |
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type: recall |
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value: 0.9365401332946972 |
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- name: F1 |
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type: f1 |
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value: 0.9284688307957485 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9929549534505072 |
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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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# ner_peoples_daily |
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This model is a fine-tuned version of [hfl/rbt6](https://huggingface.co/hfl/rbt6) on the peoples_daily_ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0249 |
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- Precision: 0.9205 |
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- Recall: 0.9365 |
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- F1: 0.9285 |
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- Accuracy: 0.9930 |
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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: 128 |
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- eval_batch_size: 128 |
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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: 8 |
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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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| 0.3154 | 1.0 | 164 | 0.0410 | 0.8258 | 0.8684 | 0.8466 | 0.9868 | |
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| 0.0394 | 2.0 | 328 | 0.0287 | 0.8842 | 0.9070 | 0.8954 | 0.9905 | |
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| 0.0293 | 3.0 | 492 | 0.0264 | 0.8978 | 0.9168 | 0.9072 | 0.9916 | |
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| 0.02 | 4.0 | 656 | 0.0254 | 0.9149 | 0.9226 | 0.9188 | 0.9923 | |
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| 0.016 | 5.0 | 820 | 0.0250 | 0.9167 | 0.9281 | 0.9224 | 0.9927 | |
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| 0.0124 | 6.0 | 984 | 0.0252 | 0.9114 | 0.9328 | 0.9220 | 0.9928 | |
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| 0.0108 | 7.0 | 1148 | 0.0249 | 0.9169 | 0.9339 | 0.9254 | 0.9928 | |
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| 0.0097 | 8.0 | 1312 | 0.0249 | 0.9205 | 0.9365 | 0.9285 | 0.9930 | |
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### Framework versions |
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- Transformers 4.23.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.5.2 |
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- Tokenizers 0.13.1 |
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