README.md

metadata

library_name: transformers
license: mit
base_model: AnonymousCS/populism_xlmr_large
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: populism_classifier_bsample_212
    results: []

populism_classifier_bsample_212

This model is a fine-tuned version of AnonymousCS/populism_xlmr_large on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2752
• Accuracy: 0.9801
• 1-f1: 0.0
• 1-recall: 0.0
• 1-precision: 0.0
• Balanced Acc: 0.5

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-06
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.06
• num_epochs: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	1-f1	1-recall	1-precision	Balanced Acc
0.6258	1.0	29	0.3913	0.9801	0.0	0.0	0.0	0.5
0.6476	2.0	58	0.3397	0.9801	0.0	0.0	0.0	0.5
0.5355	3.0	87	0.3180	0.9801	0.0	0.0	0.0	0.5
0.6818	4.0	116	0.3074	0.9801	0.0	0.0	0.0	0.5
0.4494	5.0	145	0.2971	0.9801	0.0	0.0	0.0	0.5
0.652	6.0	174	0.2886	0.9801	0.0	0.0	0.0	0.5
0.8645	7.0	203	0.2775	0.9801	0.0	0.0	0.0	0.5
0.7489	8.0	232	0.2806	0.9801	0.0	0.0	0.0	0.5
0.5238	9.0	261	0.2815	0.9801	0.0	0.0	0.0	0.5
0.5113	10.0	290	0.2797	0.9801	0.0	0.0	0.0	0.5
0.5769	11.0	319	0.2755	0.9801	0.0	0.0	0.0	0.5
0.592	12.0	348	0.2747	0.9801	0.0	0.0	0.0	0.5
0.513	13.0	377	0.2757	0.9801	0.0	0.0	0.0	0.5
0.4696	14.0	406	0.2750	0.9801	0.0	0.0	0.0	0.5
0.5106	15.0	435	0.2752	0.9801	0.0	0.0	0.0	0.5

Framework versions

• Transformers 4.46.3
• Pytorch 2.4.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3