bert-seq-class-values-no-context_plus

DayCardoso/bert-seq-class-values-no-context_plus

bert-seq-class-values-no-context_plus is a text classification model from DayCardoso. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

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

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Jul 17, 2025
Updated: Jul 17, 2025
SHA: 52dec794

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Base models

google-bert/bert-base-uncased

Model card

From the Hugging Face model README

bert-seq-class-values-no-context_plus

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

Loss: 0.3789
Subset Accuracy: 0.2907
F1 Macro: 0.3225
F1 Micro: 0.3837
Precision Macro: 0.3470
Recall Macro: 0.3052
Roc Auc: 0.7784

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: 0.0001
train_batch_size: 16
eval_batch_size: 16
seed: 2025
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.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: 0.1
num_epochs: 25
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Subset Accuracy	F1 Macro	F1 Micro	Precision Macro	Recall Macro	Roc Auc
0.3261	1.0	767	0.1848	0.0358	0.0273	0.0682	0.1322	0.0165	0.7523
0.1653	2.0	1534	0.1687	0.2000	0.1740	0.3048	0.3058	0.1429	0.8180
0.1422	3.0	2301	0.1700	0.2427	0.2509	0.3398	0.4408	0.1957	0.8239
0.1091	4.0	3068	0.1864	0.3055	0.2801	0.3921	0.4249	0.2469	0.8166
0.0806	5.0	3835	0.2045	0.3021	0.2926	0.3841	0.3993	0.2540	0.8079
0.0542	6.0	4602	0.2328	0.2992	0.2961	0.3785	0.3630	0.2644	0.7991
0.0434	7.0	5369	0.2475	0.2842	0.3076	0.3845	0.3510	0.2955	0.7982
0.0311	8.0	6136	0.2661	0.2919	0.3236	0.3904	0.3442	0.3168	0.7920
0.025	9.0	6903	0.2812	0.2844	0.3201	0.3858	0.3441	0.3085	0.7878
0.0186	10.0	7670	0.3123	0.2826	0.3246	0.3879	0.3432	0.3220	0.7827
0.0152	11.0	8437	0.3156	0.2689	0.3217	0.3774	0.3374	0.3157	0.7828
0.0109	12.0	9204	0.3380	0.2856	0.3127	0.3800	0.3410	0.2994	0.7785
0.0095	13.0	9971	0.3636	0.2684	0.3187	0.3783	0.3385	0.3140	0.7699
0.0063	14.0	10738	0.3684	0.2835	0.3206	0.3807	0.3478	0.3049	0.7755
0.0054	15.0	11505	0.3789	0.2907	0.3225	0.3837	0.3470	0.3052	0.7784

Framework versions

Transformers 4.53.2
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.2

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Jul 17, 2025
Updated: Jul 17, 2025