AnonymousCS/populism_classifier_414

1---2library_name: transformers3license: apache-2.04base_model: google/rembert5tags:6- generated_from_trainer7metrics:8- accuracy9model-index:10- name: populism_classifier_41411  results: []12---13 14<!-- This model card has been generated automatically according to the information the Trainer had access to. You15should probably proofread and complete it, then remove this comment. -->16 17# populism_classifier_41418 19This model is a fine-tuned version of [google/rembert](https://huggingface.co/google/rembert) on the None dataset.20It achieves the following results on the evaluation set:21- Loss: 0.634922- Accuracy: 0.940623- 1-f1: 0.024- 1-recall: 0.025- 1-precision: 0.026- Balanced Acc: 0.527 28## Model description29 30More information needed31 32## Intended uses & limitations33 34More information needed35 36## Training and evaluation data37 38More information needed39 40## Training procedure41 42### Training hyperparameters43 44The following hyperparameters were used during training:45- learning_rate: 1e-0546- train_batch_size: 1647- eval_batch_size: 3248- seed: 4249- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments50- lr_scheduler_type: linear51- lr_scheduler_warmup_ratio: 0.0652- num_epochs: 2053- mixed_precision_training: Native AMP54 55### Training results56 57| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1   | 1-recall | 1-precision | Balanced Acc |58|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|59| 0.4007        | 1.0   | 122  | 0.6496          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |60| 0.4705        | 2.0   | 244  | 0.7770          | 0.1291   | 0.1127 | 0.9310   | 0.06        | 0.5047       |61| 0.9942        | 3.0   | 366  | 1.1307          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |62| 0.4023        | 4.0   | 488  | 0.6234          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |63| 0.729         | 5.0   | 610  | 0.6717          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |64| 0.4101        | 6.0   | 732  | 0.6214          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |65| 0.5957        | 7.0   | 854  | 0.6215          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |66| 0.8498        | 8.0   | 976  | 0.6333          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |67| 0.5553        | 9.0   | 1098 | 0.6267          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |68| 0.4796        | 10.0  | 1220 | 0.6599          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |69| 0.6643        | 11.0  | 1342 | 0.6213          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |70| 0.5396        | 12.0  | 1464 | 0.6218          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |71| 0.5217        | 13.0  | 1586 | 0.6359          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |72| 0.5086        | 14.0  | 1708 | 0.6403          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |73| 0.6382        | 15.0  | 1830 | 0.6269          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |74| 0.7726        | 16.0  | 1952 | 0.6349          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |75 76 77### Framework versions78 79- Transformers 4.46.380- Pytorch 2.4.1+cu12181- Datasets 3.1.082- Tokenizers 0.20.383