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AnonymousCS
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populism_classifier_bsample_177

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 -16
  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: 0.9446
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- - Accuracy: 0.7608
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- - 1-f1: 0.4258
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- - 1-recall: 0.8684
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- - 1-precision: 0.2821
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- - Balanced Acc: 0.8085
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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: 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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- | 0.0744 | 1.0 | 12 | 1.3029 | 0.4220 | 0.2612 | 1.0 | 0.1502 | 0.6781 |
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- | 0.0818 | 2.0 | 24 | 1.1527 | 0.5618 | 0.3180 | 1.0 | 0.1891 | 0.7560 |
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- | 0.4693 | 3.0 | 36 | 1.1489 | 0.6022 | 0.3393 | 1.0 | 0.2043 | 0.7784 |
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- | 0.0362 | 4.0 | 48 | 0.9746 | 0.6022 | 0.3393 | 1.0 | 0.2043 | 0.7784 |
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- | 0.0553 | 5.0 | 60 | 0.8777 | 0.7392 | 0.4121 | 0.8947 | 0.2677 | 0.8081 |
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- | 0.0625 | 6.0 | 72 | 0.9100 | 0.7392 | 0.4049 | 0.8684 | 0.264 | 0.7965 |
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- | 0.0429 | 7.0 | 84 | 0.9446 | 0.7608 | 0.4258 | 0.8684 | 0.2821 | 0.8085 |
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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: 0.8398
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+ - Accuracy: 0.6667
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+ - 1-f1: 0.3737
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+ - 1-recall: 0.9737
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+ - 1-precision: 0.2313
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+ - Balanced Acc: 0.8027
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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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+ | 0.0609 | 1.0 | 6 | 0.6332 | 0.8333 | 0.4833 | 0.7632 | 0.3537 | 0.8022 |
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+ | 0.8549 | 2.0 | 12 | 0.7615 | 0.8575 | 0.4952 | 0.6842 | 0.3881 | 0.7807 |
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+ | 0.0866 | 3.0 | 18 | 0.8398 | 0.6667 | 0.3737 | 0.9737 | 0.2313 | 0.8027 |
 
 
 
 
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  ### Framework versions
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