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populism_classifier_357

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

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  1. README.md +15 -11
  2. model.safetensors +1 -1
  3. 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 [AnonymousCS/populism_english_bert_base_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_base_uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2416
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- - Accuracy: 0.9647
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- - 1-f1: 0.5581
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- - 1-recall: 0.6316
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- - 1-precision: 0.5
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- - Balanced Acc: 0.8042
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 1e-05
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- - train_batch_size: 128
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- - eval_batch_size: 128
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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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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- | 0.1159 | 1.0 | 17 | 0.1462 | 0.9442 | 0.5455 | 0.9474 | 0.3830 | 0.9457 |
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- | 0.1063 | 2.0 | 34 | 0.2492 | 0.9610 | 0.5333 | 0.6316 | 0.4615 | 0.8023 |
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- | 0.0421 | 3.0 | 51 | 0.2416 | 0.9647 | 0.5581 | 0.6316 | 0.5 | 0.8042 |
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_base_uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1747
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+ - Accuracy: 0.9814
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+ - 1-f1: 0.7727
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+ - 1-recall: 0.8947
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+ - 1-precision: 0.68
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+ - Balanced Acc: 0.9397
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 1e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
 
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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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+ | 0.2952 | 1.0 | 34 | 0.1568 | 0.9796 | 0.7556 | 0.8947 | 0.6538 | 0.9387 |
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+ | 0.0461 | 2.0 | 68 | 0.2817 | 0.9721 | 0.5714 | 0.5263 | 0.625 | 0.7574 |
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+ | 0.0239 | 3.0 | 102 | 0.1524 | 0.9777 | 0.7273 | 0.8421 | 0.64 | 0.9124 |
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+ | 0.0233 | 4.0 | 136 | 0.1413 | 0.9703 | 0.6800 | 0.8947 | 0.5484 | 0.9339 |
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+ | 0.0005 | 5.0 | 170 | 0.3419 | 0.9777 | 0.6667 | 0.6316 | 0.7059 | 0.8110 |
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+ | 0.0005 | 6.0 | 204 | 0.1759 | 0.9814 | 0.7727 | 0.8947 | 0.68 | 0.9397 |
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+ | 0.0004 | 7.0 | 238 | 0.1747 | 0.9814 | 0.7727 | 0.8947 | 0.68 | 0.9397 |
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  ### Framework versions
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