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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: AnonymousCS/populism_xlmr_base
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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_classifier_bsample_187
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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_classifier_bsample_187
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+
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+ This model is a fine-tuned version of [AnonymousCS/populism_xlmr_base](https://huggingface.co/AnonymousCS/populism_xlmr_base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7374
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+ - Accuracy: 0.0359
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+ - 1-f1: 0.0693
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+ - 1-recall: 1.0
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+ - 1-precision: 0.0359
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+ - Balanced Acc: 0.5
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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-06
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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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+ - lr_scheduler_warmup_ratio: 0.06
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+ - num_epochs: 15
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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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+ | 0.7144 | 1.0 | 13 | 0.7651 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+ | 0.7109 | 2.0 | 26 | 0.7570 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+ | 0.7222 | 3.0 | 39 | 0.7542 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+ | 0.6849 | 4.0 | 52 | 0.7506 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+ | 0.7012 | 5.0 | 65 | 0.7478 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+ | 0.7035 | 6.0 | 78 | 0.7465 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+ | 0.6665 | 7.0 | 91 | 0.7447 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+ | 0.7684 | 8.0 | 104 | 0.7451 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+ | 0.7179 | 9.0 | 117 | 0.7447 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+ | 0.6673 | 10.0 | 130 | 0.7428 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+ | 0.7015 | 11.0 | 143 | 0.7410 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+ | 0.6969 | 12.0 | 156 | 0.7392 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+ | 0.7305 | 13.0 | 169 | 0.7378 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+ | 0.699 | 14.0 | 182 | 0.7374 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+ | 0.7246 | 15.0 | 195 | 0.7374 | 0.0359 | 0.0693 | 1.0 | 0.0359 | 0.5 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.3
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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