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populism_classifier_372

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

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  1. README.md +12 -10
  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_large_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_large_uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0984
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  - Accuracy: 0.9857
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- - 1-f1: 0.9091
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- - 1-recall: 0.9259
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- - 1-precision: 0.8929
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- - Balanced Acc: 0.9583
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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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- | 0.2378 | 1.0 | 11 | 0.0675 | 0.9828 | 0.8966 | 0.9630 | 0.8387 | 0.9737 |
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- | 0.1786 | 2.0 | 22 | 0.0842 | 0.9828 | 0.8929 | 0.9259 | 0.8621 | 0.9568 |
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- | 0.0906 | 3.0 | 33 | 0.0984 | 0.9857 | 0.9091 | 0.9259 | 0.8929 | 0.9583 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_large_uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3161
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  - Accuracy: 0.9857
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+ - 1-f1: 0.9057
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+ - 1-recall: 0.8889
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+ - 1-precision: 0.9231
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+ - Balanced Acc: 0.9413
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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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+ | 0.3105 | 1.0 | 22 | 0.1109 | 0.9542 | 0.7647 | 0.9630 | 0.6341 | 0.9582 |
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+ | 0.0309 | 2.0 | 44 | 0.0905 | 0.9857 | 0.9123 | 0.9630 | 0.8667 | 0.9753 |
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+ | 0.0059 | 3.0 | 66 | 0.1699 | 0.9799 | 0.8727 | 0.8889 | 0.8571 | 0.9382 |
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+ | 0.0009 | 4.0 | 88 | 0.4152 | 0.9771 | 0.84 | 0.7778 | 0.9130 | 0.8858 |
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+ | 0.0004 | 5.0 | 110 | 0.3161 | 0.9857 | 0.9057 | 0.8889 | 0.9231 | 0.9413 |
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  ### Framework versions
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