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populism_classifier_100

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_02-39-00_ebae452a3ad2/events.out.tfevents.1756175941.ebae452a3ad2.1874.5 +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 [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: 0.3452
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- - Accuracy: 0.9339
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- - 1-f1: 0.6571
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- - 1-recall: 0.7188
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- - 1-precision: 0.6053
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- - Balanced Acc: 0.8367
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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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- | 0.3004 | 1.0 | 12 | 0.2099 | 0.8760 | 0.5872 | 1.0 | 0.4156 | 0.9320 |
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- | 0.2548 | 2.0 | 24 | 0.2211 | 0.9174 | 0.6512 | 0.875 | 0.5185 | 0.8982 |
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- | 0.1285 | 3.0 | 36 | 0.3452 | 0.9339 | 0.6571 | 0.7188 | 0.6053 | 0.8367 |
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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: 0.4632
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+ - Accuracy: 0.9634
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+ - 1-f1: 0.5333
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+ - 1-recall: 0.5
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+ - 1-precision: 0.5714
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+ - Balanced Acc: 0.7418
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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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+ | 0.29 | 1.0 | 12 | 0.3524 | 0.8979 | 0.3607 | 0.6875 | 0.2444 | 0.7973 |
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+ | 0.3206 | 2.0 | 24 | 0.4495 | 0.9450 | 0.4 | 0.4375 | 0.3684 | 0.7024 |
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+ | 0.3902 | 3.0 | 36 | 0.4632 | 0.9634 | 0.5333 | 0.5 | 0.5714 | 0.7418 |
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  ### Framework versions
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