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doyoungkim
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bert-base-uncased-sst2-membership-attack

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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add model

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  1. README.md +7 -7
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -15,8 +15,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unkown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2233
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- - Accuracy: 0.9186
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  ## Model description
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@@ -47,11 +47,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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- | 0.5101 | 1.0 | 3813 | 0.2539 | 0.9140 |
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- | 0.5051 | 2.0 | 7626 | 0.2499 | 0.9117 |
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- | 0.5006 | 3.0 | 11439 | 0.2452 | 0.9071 |
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- | 0.503 | 4.0 | 15252 | 0.2265 | 0.9151 |
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- | 0.4989 | 5.0 | 19065 | 0.2233 | 0.9186 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unkown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6296
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+ - Accuracy: 0.8681
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.6921 | 1.0 | 3813 | 0.6263 | 0.8360 |
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+ | 0.6916 | 2.0 | 7626 | 0.6296 | 0.8681 |
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+ | 0.6904 | 3.0 | 11439 | 0.6105 | 0.8406 |
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+ | 0.6886 | 4.0 | 15252 | 0.6192 | 0.8200 |
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+ | 0.6845 | 5.0 | 19065 | 0.6250 | 0.7798 |
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  ### Framework versions
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