xlmr_all_immigration4

AnonymousCS/xlmr_all_immigration4

xlmr_all_immigration4 is a text classification model from AnonymousCS. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
License: mit
Model type: xlm-roberta
Access: Public
Created: Aug 19, 2025
Updated: Aug 19, 2025
SHA: 6bebfa66

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Base models

FacebookAI/xlm-roberta-large

Model card

From the Hugging Face model README

xlmr_all_immigration4

This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3429
Accuracy: 0.9
1-f1: 0.8354
1-recall: 0.7674
1-precision: 0.9167
Balanced Acc: 0.8665

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: 128
eval_batch_size: 128
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
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
0.601	1.0	5	0.6534	0.6692	0.0	0.0	0.0	0.5
0.6427	2.0	10	0.6305	0.6692	0.0	0.0	0.0	0.5
0.6068	3.0	15	0.6400	0.6692	0.0	0.0	0.0	0.5
0.7139	4.0	20	0.6143	0.6692	0.0	0.0	0.0	0.5
0.5395	5.0	25	0.5969	0.6692	0.0	0.0	0.0	0.5
0.5974	6.0	30	0.5701	0.7	0.1702	0.0930	1.0	0.5465
0.5214	7.0	35	0.5203	0.8077	0.5902	0.4186	1.0	0.7093
0.4061	8.0	40	0.4794	0.8615	0.7429	0.6047	0.9630	0.7966
0.4453	9.0	45	0.4435	0.8692	0.7671	0.6512	0.9333	0.8141
0.3981	10.0	50	0.4033	0.8692	0.7848	0.7209	0.8611	0.8317
0.4108	11.0	55	0.3717	0.8923	0.8205	0.7442	0.9143	0.8549
0.226	12.0	60	0.3681	0.8769	0.8049	0.7674	0.8462	0.8492
0.3163	13.0	65	0.3546	0.8846	0.8148	0.7674	0.8684	0.8550
0.2189	14.0	70	0.3438	0.8923	0.8205	0.7442	0.9143	0.8549
0.2799	15.0	75	0.3429	0.9	0.8354	0.7674	0.9167	0.8665

Framework versions

Transformers 4.56.0.dev0
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.21.4

Task: Text Classification
Library: transformers
Type: xlm-roberta
License: mit
Created: Aug 19, 2025
Updated: Aug 19, 2025