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populism_classifier_102

Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
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/Aug26_02-42-05_ebae452a3ad2/events.out.tfevents.1756176125.ebae452a3ad2.1874.7 +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 [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3588
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- - Accuracy: 0.9327
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- - 1-f1: 0.6562
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- - 1-recall: 0.8077
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- - 1-precision: 0.5526
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- - Balanced Acc: 0.8756
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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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- | 0.281 | 1.0 | 11 | 0.2403 | 0.8991 | 0.5479 | 0.7692 | 0.4255 | 0.8398 |
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- | 0.1745 | 2.0 | 22 | 0.3129 | 0.9297 | 0.6462 | 0.8077 | 0.5385 | 0.8739 |
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- | 0.1745 | 3.0 | 33 | 0.3588 | 0.9327 | 0.6562 | 0.8077 | 0.5526 | 0.8756 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6197
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+ - Accuracy: 0.9344
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+ - 1-f1: 0.4483
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+ - 1-recall: 0.4483
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+ - 1-precision: 0.4483
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+ - Balanced Acc: 0.7067
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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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+ | 0.4263 | 1.0 | 16 | 0.4514 | 0.9180 | 0.4737 | 0.6207 | 0.3830 | 0.7788 |
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+ | 0.2493 | 2.0 | 32 | 0.6051 | 0.9303 | 0.4688 | 0.5172 | 0.4286 | 0.7368 |
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+ | 0.1688 | 3.0 | 48 | 0.6197 | 0.9344 | 0.4483 | 0.4483 | 0.4483 | 0.7067 |
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  ### Framework versions
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