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populism_classifier_004

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

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  1. README.md +8 -7
  2. model.safetensors +1 -1
  3. runs/Aug25_19-19-19_2e8e96a3dcb3/events.out.tfevents.1756149560.2e8e96a3dcb3.2911.4 +3 -0
  4. 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 [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2398
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  - Accuracy: 0.9833
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- - 1-f1: 0.5
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- - 1-recall: 0.5
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  - 1-precision: 0.5
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- - Balanced Acc: 0.7458
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  ## Model description
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@@ -55,9 +55,10 @@ The following hyperparameters were used during training:
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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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- | 0.2159 | 1.0 | 57 | 0.1652 | 0.9699 | 0.4130 | 0.6333 | 0.3065 | 0.8045 |
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- | 0.2815 | 2.0 | 114 | 0.3137 | 0.9855 | 0.4348 | 0.3333 | 0.625 | 0.6650 |
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- | 0.2949 | 3.0 | 171 | 0.2398 | 0.9833 | 0.5 | 0.5 | 0.5 | 0.7458 |
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2928
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  - Accuracy: 0.9833
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+ - 1-f1: 0.5312
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+ - 1-recall: 0.5667
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  - 1-precision: 0.5
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+ - Balanced Acc: 0.7785
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  ## Model description
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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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+ | 0.2697 | 1.0 | 57 | 0.1656 | 0.9855 | 0.5806 | 0.6 | 0.5625 | 0.7960 |
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+ | 0.0992 | 2.0 | 114 | 0.1429 | 0.9699 | 0.46 | 0.7667 | 0.3286 | 0.8700 |
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+ | 0.1229 | 3.0 | 171 | 0.1970 | 0.9805 | 0.4776 | 0.5333 | 0.4324 | 0.7607 |
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+ | 0.0171 | 4.0 | 228 | 0.2928 | 0.9833 | 0.5312 | 0.5667 | 0.5 | 0.7785 |
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  ### Framework versions
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