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Misinformation-Covid-bert-base-chinese

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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  1. README.md +12 -12
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.6859
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- - F1: 0.3191
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  ## Model description
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@@ -48,16 +48,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.6995 | 1.0 | 201 | 0.6661 | 0.0417 |
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- | 0.6843 | 2.0 | 402 | 0.6824 | 0.2745 |
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- | 0.665 | 3.0 | 603 | 0.6240 | 0.3306 |
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- | 0.6208 | 4.0 | 804 | 0.6211 | 0.3141 |
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- | 0.5939 | 5.0 | 1005 | 0.6095 | 0.3231 |
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- | 0.6094 | 6.0 | 1206 | 0.6216 | 0.3276 |
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- | 0.5177 | 7.0 | 1407 | 0.6437 | 0.3333 |
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- | 0.5092 | 8.0 | 1608 | 0.6585 | 0.3519 |
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- | 0.4781 | 9.0 | 1809 | 0.6867 | 0.3333 |
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- | 0.4706 | 10.0 | 2010 | 0.6859 | 0.3191 |
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  ### Framework versions
 
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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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  | 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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