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End of training

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  1. README.md +68 -0
  2. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: AnonymousCS/populism_english_bert_base_uncased
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: populism_model266
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # populism_model266
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+
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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: 0.4223
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+ - Accuracy: 0.9605
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+ - 1-f1: 0.1702
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+ - 1-recall: 0.1429
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+ - 1-precision: 0.2105
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+ - Balanced Acc: 0.5636
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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 OptimizerNames.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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+ - num_epochs: 3
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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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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+ | 0.4482 | 1.0 | 62 | 0.4282 | 0.9585 | 0.2264 | 0.2143 | 0.24 | 0.5972 |
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+ | 0.5014 | 2.0 | 124 | 0.3894 | 0.9534 | 0.2333 | 0.25 | 0.2188 | 0.6120 |
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+ | 0.3433 | 3.0 | 186 | 0.4223 | 0.9605 | 0.1702 | 0.1429 | 0.2105 | 0.5636 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.49.0.dev0
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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