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populism_classifier_bsample_167

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 +17 -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_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: 0.8409
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- - Accuracy: 0.8240
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- - 1-f1: 0.3899
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- - 1-recall: 0.9688
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- - 1-precision: 0.2441
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- - Balanced Acc: 0.8919
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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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- | 0.1239 | 1.0 | 12 | 0.8040 | 0.6751 | 0.2634 | 1.0 | 0.1517 | 0.8276 |
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- | 0.0496 | 2.0 | 24 | 0.4316 | 0.8639 | 0.4444 | 0.9375 | 0.2913 | 0.8984 |
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- | 0.0208 | 3.0 | 36 | 0.5367 | 0.9183 | 0.4944 | 0.6875 | 0.3860 | 0.8100 |
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- | 0.0536 | 4.0 | 48 | 0.8409 | 0.8240 | 0.3899 | 0.9688 | 0.2441 | 0.8919 |
 
 
 
 
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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: 0.3828
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+ - Accuracy: 0.9056
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+ - 1-f1: 0.5273
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+ - 1-recall: 0.9062
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+ - 1-precision: 0.3718
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+ - Balanced Acc: 0.9059
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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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+ | 0.0543 | 1.0 | 6 | 0.4610 | 0.9310 | 0.5581 | 0.75 | 0.4444 | 0.8461 |
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+ | 0.0721 | 2.0 | 12 | 0.4254 | 0.9201 | 0.5217 | 0.75 | 0.4 | 0.8403 |
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+ | 0.0486 | 3.0 | 18 | 0.4625 | 0.8566 | 0.4476 | 1.0 | 0.2883 | 0.9239 |
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+ | 0.0197 | 4.0 | 24 | 0.3800 | 0.8966 | 0.5289 | 1.0 | 0.3596 | 0.9451 |
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+ | 0.0071 | 5.0 | 30 | 0.3595 | 0.9056 | 0.5094 | 0.8438 | 0.3649 | 0.8766 |
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+ | 0.0302 | 6.0 | 36 | 0.3587 | 0.9038 | 0.5225 | 0.9062 | 0.3671 | 0.9050 |
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+ | 0.0069 | 7.0 | 42 | 0.3618 | 0.9056 | 0.5185 | 0.875 | 0.3684 | 0.8913 |
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+ | 0.0029 | 8.0 | 48 | 0.3828 | 0.9056 | 0.5273 | 0.9062 | 0.3718 | 0.9059 |
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  ### Framework versions
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