AnonymousCS/populism_classifier_bsample_211

1---2library_name: transformers3license: mit4base_model: AnonymousCS/populism_xlmr_large5tags:6- generated_from_trainer7metrics:8- accuracy9model-index:10- name: populism_classifier_bsample_21111  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_bsample_21118 19This model is a fine-tuned version of [AnonymousCS/populism_xlmr_large](https://huggingface.co/AnonymousCS/populism_xlmr_large) on the None dataset.20It achieves the following results on the evaluation set:21- Loss: 0.816822- Accuracy: 0.085523- 1-f1: 0.157524- 1-recall: 1.025- 1-precision: 0.085526- 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-0646- train_batch_size: 1647- eval_batch_size: 1648- 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: 1553- 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| 0.6808        | 1.0   | 11   | 0.7414          | 0.0855   | 0.1575 | 1.0      | 0.0855      | 0.5          |60| 0.7473        | 2.0   | 22   | 0.7767          | 0.0855   | 0.1575 | 1.0      | 0.0855      | 0.5          |61| 0.7377        | 3.0   | 33   | 0.7940          | 0.0855   | 0.1575 | 1.0      | 0.0855      | 0.5          |62| 0.8351        | 4.0   | 44   | 0.7990          | 0.0855   | 0.1575 | 1.0      | 0.0855      | 0.5          |63| 0.7401        | 5.0   | 55   | 0.8055          | 0.0855   | 0.1575 | 1.0      | 0.0855      | 0.5          |64| 0.758         | 6.0   | 66   | 0.8168          | 0.0855   | 0.1575 | 1.0      | 0.0855      | 0.5          |65 66 67### Framework versions68 69- Transformers 4.46.370- Pytorch 2.4.1+cu12171- Datasets 3.1.072- Tokenizers 0.20.373