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populism_classifier_355

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 +13 -13
  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: 0.2728
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- - Accuracy: 0.9506
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- - 1-f1: 0.6364
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- - 1-recall: 0.75
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- - 1-precision: 0.5526
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- - Balanced Acc: 0.8564
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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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- | 0.2313 | 1.0 | 16 | 0.4371 | 0.9568 | 0.5714 | 0.5 | 0.6667 | 0.7424 |
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- | 0.2233 | 2.0 | 32 | 0.2298 | 0.8765 | 0.4643 | 0.9286 | 0.3095 | 0.9010 |
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- | 0.1951 | 3.0 | 48 | 0.2228 | 0.9012 | 0.5102 | 0.8929 | 0.3571 | 0.8973 |
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- | 0.1782 | 4.0 | 64 | 0.2232 | 0.9198 | 0.5618 | 0.8929 | 0.4098 | 0.9071 |
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- | 0.0679 | 5.0 | 80 | 0.2728 | 0.9506 | 0.6364 | 0.75 | 0.5526 | 0.8564 |
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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: 1.0070
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+ - Accuracy: 0.9568
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+ - 1-f1: 0.4878
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+ - 1-recall: 0.3571
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+ - 1-precision: 0.7692
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+ - Balanced Acc: 0.6753
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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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+ | 0.3888 | 1.0 | 31 | 0.3173 | 0.9609 | 0.6122 | 0.5357 | 0.7143 | 0.7613 |
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+ | 0.1127 | 2.0 | 62 | 0.1631 | 0.9568 | 0.7200 | 0.9643 | 0.5745 | 0.9603 |
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+ | 0.1928 | 3.0 | 93 | 0.2718 | 0.9547 | 0.6333 | 0.6786 | 0.5938 | 0.8251 |
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+ | 0.2627 | 4.0 | 124 | 0.4180 | 0.9650 | 0.6909 | 0.6786 | 0.7037 | 0.8306 |
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+ | 0.0078 | 5.0 | 155 | 1.0070 | 0.9568 | 0.4878 | 0.3571 | 0.7692 | 0.6753 |
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  ### Framework versions
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