AnonymousCS/populism_classifier_bsample_086

1---2library_name: transformers3license: mit4base_model: FacebookAI/xlm-roberta-base5tags:6- generated_from_trainer7metrics:8- accuracy9model-index:10- name: populism_classifier_bsample_08611  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_08618 19This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.20It achieves the following results on the evaluation set:21- Loss: 0.913122- Accuracy: 0.828723- 1-f1: 0.396024- 1-recall: 1.025- 1-precision: 0.246926- Balanced Acc: 0.909227 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: 3e-0546- 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- num_epochs: 1552- mixed_precision_training: Native AMP53 54### Training results55 56| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1   | 1-recall | 1-precision | Balanced Acc |57|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|58| 0.0089        | 1.0   | 12   | 0.8364          | 0.7921   | 0.3509 | 1.0      | 0.2128      | 0.8899       |59| 0.0059        | 2.0   | 24   | 0.6757          | 0.8539   | 0.4348 | 1.0      | 0.2778      | 0.9226       |60| 0.0034        | 3.0   | 36   | 0.6007          | 0.8961   | 0.5067 | 0.95     | 0.3455      | 0.9214       |61| 0.0022        | 4.0   | 48   | 0.9966          | 0.8202   | 0.3846 | 1.0      | 0.2381      | 0.9048       |62| 0.0027        | 5.0   | 60   | 0.9131          | 0.8287   | 0.3960 | 1.0      | 0.2469      | 0.9092       |63 64 65### Framework versions66 67- Transformers 4.46.368- Pytorch 2.4.1+cu12169- Datasets 3.1.070- Tokenizers 0.20.371