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AnonymousCS
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populism_classifier_bsample_179

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 +12 -12
  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_multilingual_bert_uncased_v2](https://huggingface.co/AnonymousCS/populism_multilingual_bert_uncased_v2) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6902
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- - Accuracy: 0.7492
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- - 1-f1: 0.3594
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- - 1-recall: 0.92
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- - 1-precision: 0.2233
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- - Balanced Acc: 0.8275
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  ## Model description
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@@ -42,9 +42,9 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 3e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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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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- | 0.138 | 1.0 | 11 | 0.6539 | 0.5229 | 0.2427 | 1.0 | 0.1381 | 0.7417 |
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- | 1.0586 | 2.0 | 22 | 1.2234 | 0.5872 | 0.2703 | 1.0 | 0.1562 | 0.7765 |
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- | 0.4486 | 3.0 | 33 | 0.6902 | 0.7492 | 0.3594 | 0.92 | 0.2233 | 0.8275 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [AnonymousCS/populism_multilingual_bert_uncased_v2](https://huggingface.co/AnonymousCS/populism_multilingual_bert_uncased_v2) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7519
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+ - Accuracy: 0.7615
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+ - 1-f1: 0.3906
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+ - 1-recall: 1.0
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+ - 1-precision: 0.2427
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+ - Balanced Acc: 0.8709
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  ## Model description
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  ### Training hyperparameters
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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: 32
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+ - eval_batch_size: 32
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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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+ | 0.0873 | 1.0 | 6 | 0.7139 | 0.7431 | 0.3731 | 1.0 | 0.2294 | 0.8609 |
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+ | 0.1897 | 2.0 | 12 | 0.8471 | 0.7309 | 0.3623 | 1.0 | 0.2212 | 0.8543 |
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+ | 0.0591 | 3.0 | 18 | 0.7519 | 0.7615 | 0.3906 | 1.0 | 0.2427 | 0.8709 |
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  ### Framework versions
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