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populism_classifier_bsample_160

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

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  1. README.md +8 -9
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,7 +18,7 @@ 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: 0.4024
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  - Accuracy: 0.9512
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  - 1-f1: 0.2951
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  - 1-recall: 0.5143
@@ -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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- | 0.2822 | 1.0 | 29 | 0.3105 | 0.9137 | 0.2165 | 0.6 | 0.1321 | 0.7600 |
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- | 0.9092 | 2.0 | 58 | 0.5246 | 0.7876 | 0.1538 | 0.9714 | 0.0835 | 0.8777 |
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- | 0.3792 | 3.0 | 87 | 0.2824 | 0.9568 | 0.2963 | 0.4571 | 0.2192 | 0.7121 |
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- | 0.0906 | 4.0 | 116 | 0.9478 | 0.7905 | 0.1478 | 0.9143 | 0.0804 | 0.8511 |
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- | 0.3919 | 5.0 | 145 | 0.4024 | 0.9512 | 0.2951 | 0.5143 | 0.2069 | 0.7372 |
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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: 0.4105
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  - Accuracy: 0.9512
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  - 1-f1: 0.2951
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  - 1-recall: 0.5143
 
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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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+ | 0.1216 | 1.0 | 15 | 0.9502 | 0.6979 | 0.1163 | 1.0 | 0.0617 | 0.8459 |
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+ | 0.1406 | 2.0 | 30 | 0.2712 | 0.9177 | 0.2487 | 0.6857 | 0.1519 | 0.8040 |
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+ | 0.0679 | 3.0 | 45 | 0.4224 | 0.8984 | 0.2318 | 0.7714 | 0.1364 | 0.8362 |
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+ | 0.9874 | 4.0 | 60 | 0.4105 | 0.9512 | 0.2951 | 0.5143 | 0.2069 | 0.7372 |
 
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  ### Framework versions
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