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populism_classifier_402

Text Classification
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Safetensors
rembert
Generated from Trainer
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xet
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End of training

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  1. README.md +9 -14
  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 [google/rembert](https://huggingface.co/google/rembert) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6316
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  - Accuracy: 0.9332
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  - 1-f1: 0.0
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  - 1-recall: 0.0
@@ -44,7 +44,7 @@ More information needed
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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: 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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- | 0.7091 | 1.0 | 101 | 0.6356 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.5807 | 2.0 | 202 | 0.6365 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.7524 | 3.0 | 303 | 0.6308 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.7046 | 4.0 | 404 | 0.6280 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.6791 | 5.0 | 505 | 0.6315 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.718 | 6.0 | 606 | 0.6427 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.4048 | 7.0 | 707 | 0.6275 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.5765 | 8.0 | 808 | 0.6304 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.7317 | 9.0 | 909 | 0.6275 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.6877 | 10.0 | 1010 | 0.6363 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.5739 | 11.0 | 1111 | 0.6312 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.5852 | 12.0 | 1212 | 0.6316 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/rembert](https://huggingface.co/google/rembert) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6684
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  - Accuracy: 0.9332
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  - 1-f1: 0.0
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  - 1-recall: 0.0
 
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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: 16
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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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+ | 0.7055 | 1.0 | 101 | 0.6621 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.6021 | 2.0 | 202 | 0.6646 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.8043 | 3.0 | 303 | 0.6611 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.7283 | 4.0 | 404 | 0.6673 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.6756 | 5.0 | 505 | 0.6608 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.6906 | 6.0 | 606 | 0.6643 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.3813 | 7.0 | 707 | 0.6684 | 0.9332 | 0.0 | 0.0 | 0.0 | 0.5 |
 
 
 
 
 
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  ### Framework versions
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