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populism_classifier_099

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_02-37-34_ebae452a3ad2/events.out.tfevents.1756175854.ebae452a3ad2.1874.4 +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 [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: 0.3299
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- - Accuracy: 0.8990
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- - 1-f1: 0.7059
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- - 1-recall: 0.96
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- - 1-precision: 0.5581
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- - Balanced Acc: 0.9251
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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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- | 0.2574 | 1.0 | 7 | 0.2924 | 0.8838 | 0.6761 | 0.96 | 0.5217 | 0.9164 |
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- | 0.2816 | 2.0 | 14 | 0.3936 | 0.8990 | 0.6875 | 0.88 | 0.5641 | 0.8909 |
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- | 0.1332 | 3.0 | 21 | 0.3299 | 0.8990 | 0.7059 | 0.96 | 0.5581 | 0.9251 |
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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: 0.3617
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+ - Accuracy: 0.8733
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+ - 1-f1: 0.54
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+ - 1-recall: 0.8438
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+ - 1-precision: 0.3971
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+ - Balanced Acc: 0.8599
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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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+ | 0.474 | 1.0 | 12 | 0.3547 | 0.8264 | 0.4793 | 0.9062 | 0.3258 | 0.8625 |
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+ | 0.304 | 2.0 | 24 | 0.3840 | 0.8981 | 0.5747 | 0.7812 | 0.4545 | 0.8453 |
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+ | 0.2064 | 3.0 | 36 | 0.3617 | 0.8733 | 0.54 | 0.8438 | 0.3971 | 0.8599 |
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  ### Framework versions
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