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populism_classifier_416

Text Classification
Transformers
Safetensors
rembert
Generated from Trainer
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xet
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End of training

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  1. README.md +5 -6
  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: 0.6208
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  - Accuracy: 0.9371
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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
@@ -55,10 +55,9 @@ The following hyperparameters were used during training:
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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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- | 0.426 | 1.0 | 124 | 0.6199 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.5741 | 2.0 | 248 | 0.6316 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.5653 | 3.0 | 372 | 0.6448 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.5376 | 4.0 | 496 | 0.6208 | 0.9371 | 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: 0.6510
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  - Accuracy: 0.9371
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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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+ | 0.43 | 1.0 | 124 | 0.6327 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.5814 | 2.0 | 248 | 0.6407 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.5448 | 3.0 | 372 | 0.6510 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 |
 
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  ### Framework versions
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