populism_classifier_391 – AI Model by AnonymousCS | AlphaNeural AI

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populism_classifier_391

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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populism_classifier_391

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

Loss: 1.3230
Accuracy: 0.9523
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-05
train_batch_size: 16
eval_batch_size: 32
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: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	1-f1	1-recall	1-precision	Balanced Acc
0.0128	1.0	3484	0.9344	0.9523	0.0	0.0	0.0	0.5
0.9515	2.0	6968	0.8225	0.9523	0.0	0.0	0.0	0.5
0.6456	3.0	10452	0.8839	0.9523	0.0	0.0	0.0	0.5
0.053	4.0	13936	0.9211	0.9523	0.0	0.0	0.0	0.5
0.5498	5.0	17420	0.9413	0.9523	0.0	0.0	0.0	0.5
0.218	6.0	20904	0.8088	0.9523	0.0	0.0	0.0	0.5
1.9402	7.0	24388	1.1587	0.9523	0.0	0.0	0.0	0.5
0.6771	8.0	27872	1.2072	0.9523	0.0	0.0	0.0	0.5
0.6533	9.0	31356	1.4121	0.9523	0.0	0.0	0.0	0.5
0.8778	10.0	34840	1.2411	0.9523	0.0	0.0	0.0	0.5
0.4423	11.0	38324	1.3230	0.9523	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