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--- |
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base_model: bert-base-chinese |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: Misinformation-Covid-bert-base-chinese |
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results: [] |
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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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# Misinformation-Covid-bert-base-chinese |
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This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6165 |
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- F1: 0.4706 |
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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-06 |
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- train_batch_size: 8 |
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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 | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.6722 | 1.0 | 189 | 0.6155 | 0.0 | |
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| 0.6611 | 2.0 | 378 | 0.5880 | 0.2979 | |
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| 0.6133 | 3.0 | 567 | 0.5847 | 0.2727 | |
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| 0.6343 | 4.0 | 756 | 0.5573 | 0.4151 | |
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| 0.6557 | 5.0 | 945 | 0.5704 | 0.4444 | |
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| 0.5996 | 6.0 | 1134 | 0.6545 | 0.3750 | |
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| 0.6239 | 7.0 | 1323 | 0.6037 | 0.4407 | |
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| 0.6089 | 8.0 | 1512 | 0.6145 | 0.4590 | |
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| 0.555 | 9.0 | 1701 | 0.6273 | 0.4746 | |
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| 0.5281 | 10.0 | 1890 | 0.6165 | 0.4706 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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