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populism_classifier_026

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 +9 -9
  2. model.safetensors +1 -1
  3. runs/Aug25_20-23-05_9cbfd459869c/events.out.tfevents.1756153386.9cbfd459869c.1551.5 +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: 0.5366
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- - Accuracy: 0.9391
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- - 1-f1: 0.5833
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- - 1-recall: 0.6774
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- - 1-precision: 0.5122
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- - Balanced Acc: 0.8171
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  ## Model description
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@@ -55,9 +55,9 @@ 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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- | 0.3382 | 1.0 | 16 | 0.4001 | 0.9148 | 0.5333 | 0.7742 | 0.4068 | 0.8492 |
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- | 0.0961 | 2.0 | 32 | 0.4131 | 0.9391 | 0.6154 | 0.7742 | 0.5106 | 0.8622 |
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- | 0.0882 | 3.0 | 48 | 0.5366 | 0.9391 | 0.5833 | 0.6774 | 0.5122 | 0.8171 |
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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: 0.6842
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+ - Accuracy: 0.8742
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+ - 1-f1: 0.3673
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+ - 1-recall: 0.5806
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+ - 1-precision: 0.2687
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+ - Balanced Acc: 0.7373
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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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+ | 0.2853 | 1.0 | 16 | 0.6369 | 0.8783 | 0.3617 | 0.5484 | 0.2698 | 0.7244 |
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+ | 0.1173 | 2.0 | 32 | 0.7597 | 0.9026 | 0.4 | 0.5161 | 0.3265 | 0.7224 |
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+ | 0.1884 | 3.0 | 48 | 0.6842 | 0.8742 | 0.3673 | 0.5806 | 0.2687 | 0.7373 |
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  ### Framework versions
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