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populism_classifier_352

Text Classification
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Safetensors
bert
Generated from Trainer
text-embeddings-inference
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End of training

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  1. README.md +18 -13
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,12 +18,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_base_uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1808
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- - Accuracy: 0.9853
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- - 1-f1: 0.7603
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- - 1-recall: 0.8070
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- - 1-precision: 0.7188
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- - Balanced Acc: 0.8988
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 1e-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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
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- | 0.3947 | 1.0 | 62 | 0.2643 | 0.9752 | 0.608 | 0.6667 | 0.5588 | 0.8255 |
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- | 0.1432 | 2.0 | 124 | 0.1665 | 0.9413 | 0.4579 | 0.8596 | 0.3121 | 0.9017 |
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- | 0.0891 | 3.0 | 186 | 0.1553 | 0.9504 | 0.5000 | 0.8596 | 0.3525 | 0.9064 |
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- | 0.0644 | 4.0 | 248 | 0.1596 | 0.9777 | 0.6667 | 0.7719 | 0.5867 | 0.8779 |
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- | 0.1756 | 5.0 | 310 | 0.1808 | 0.9853 | 0.7603 | 0.8070 | 0.7188 | 0.8988 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_base_uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1382
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+ - Accuracy: 0.9939
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+ - 1-f1: 0.8929
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+ - 1-recall: 0.8772
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+ - 1-precision: 0.9091
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+ - Balanced Acc: 0.9373
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 1e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
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+ | 0.188 | 1.0 | 124 | 0.1878 | 0.96 | 0.5269 | 0.7719 | 0.4 | 0.8688 |
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+ | 0.0717 | 2.0 | 248 | 0.1507 | 0.9635 | 0.5663 | 0.8246 | 0.4312 | 0.8961 |
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+ | 0.0532 | 3.0 | 372 | 0.1856 | 0.9792 | 0.6555 | 0.6842 | 0.6290 | 0.8361 |
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+ | 0.0114 | 4.0 | 496 | 0.1190 | 0.9818 | 0.7391 | 0.8947 | 0.6296 | 0.9395 |
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+ | 0.001 | 5.0 | 620 | 0.1292 | 0.9833 | 0.7660 | 0.9474 | 0.6429 | 0.9659 |
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+ | 0.0012 | 6.0 | 744 | 0.1184 | 0.9899 | 0.8333 | 0.8772 | 0.7937 | 0.9352 |
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+ | 0.0013 | 7.0 | 868 | 0.1127 | 0.9853 | 0.7852 | 0.9298 | 0.6795 | 0.9584 |
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+ | 0.0005 | 8.0 | 992 | 0.1341 | 0.9853 | 0.7852 | 0.9298 | 0.6795 | 0.9584 |
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+ | 0.0003 | 9.0 | 1116 | 0.2046 | 0.9909 | 0.8393 | 0.8246 | 0.8545 | 0.9102 |
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+ | 0.0002 | 10.0 | 1240 | 0.1382 | 0.9939 | 0.8929 | 0.8772 | 0.9091 | 0.9373 |
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  ### Framework versions
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