bert-base-cased

xshubhamx/bert-base-cased

bert-base-cased is a text classification model from xshubhamx. Use it when you need a label for a piece of text. It is set up for transformers.

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

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At a glance

Task: Text Classification
Library: transformers
Model type: bert
Access: Public
Created: Apr 11, 2024
Updated: Apr 13, 2024
SHA: 58f0e5d1

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Model card

From the Hugging Face model README

bert-base-cased

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.6877
Accuracy: 0.8102
Precision: 0.8108
Recall: 0.8102
Precision Macro: 0.7633
Recall Macro: 0.7599
Macro Fpr: 0.0170
Weighted Fpr: 0.0165
Weighted Specificity: 0.9750
Macro Specificity: 0.9857
Weighted Sensitivity: 0.8102
Macro Sensitivity: 0.7599
F1 Micro: 0.8102
F1 Macro: 0.7596
F1 Weighted: 0.8098

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	Precision Macro	Recall Macro	Macro Fpr	Weighted Fpr	Weighted Specificity	Macro Specificity	Weighted Sensitivity	Macro Sensitivity	F1 Micro	F1 Macro	F1 Weighted
1.2487	1.0	643	0.8270	0.7475	0.7315	0.7475	0.5948	0.5801	0.0252	0.0236	0.9559	0.9802	0.7475	0.5801	0.7475	0.5695	0.7284
0.7012	2.0	1286	0.7203	0.7909	0.7910	0.7909	0.6785	0.6953	0.0192	0.0185	0.9718	0.9842	0.7909	0.6953	0.7909	0.6824	0.7873
0.5493	3.0	1929	0.8682	0.7909	0.7861	0.7909	0.6958	0.7065	0.0192	0.0185	0.9716	0.9842	0.7909	0.7065	0.7909	0.6985	0.7839
0.2971	4.0	2572	0.9885	0.8064	0.8093	0.8064	0.7203	0.7227	0.0174	0.0169	0.9745	0.9854	0.8064	0.7227	0.8064	0.7145	0.8039
0.2142	5.0	3215	1.1664	0.8009	0.8062	0.8009	0.7230	0.7128	0.0179	0.0174	0.9760	0.9851	0.8009	0.7128	0.8009	0.7040	0.7982
0.1312	6.0	3858	1.1734	0.7947	0.7994	0.7947	0.7368	0.7345	0.0189	0.0181	0.9731	0.9845	0.7947	0.7345	0.7947	0.7297	0.7931
0.0773	7.0	4501	1.3176	0.8071	0.8086	0.8071	0.7353	0.7467	0.0173	0.0168	0.9762	0.9856	0.8071	0.7467	0.8071	0.7367	0.8057
0.0424	8.0	5144	1.4781	0.8002	0.8034	0.8002	0.7390	0.7444	0.0181	0.0175	0.9739	0.9849	0.8002	0.7444	0.8002	0.7388	0.8000
0.0367	9.0	5787	1.5131	0.8071	0.8138	0.8071	0.7325	0.7592	0.0173	0.0168	0.9764	0.9856	0.8071	0.7592	0.8071	0.7423	0.8088
0.0235	10.0	6430	1.5637	0.8025	0.8042	0.8025	0.7678	0.7473	0.0179	0.0173	0.9736	0.9851	0.8025	0.7473	0.8025	0.7502	0.8006
0.0116	11.0	7073	1.5827	0.8156	0.8152	0.8156	0.7474	0.7546	0.0164	0.0159	0.9767	0.9862	0.8156	0.7546	0.8156	0.7458	0.8137
0.0083	12.0	7716	1.6471	0.8095	0.8087	0.8095	0.7554	0.7538	0.0172	0.0165	0.9744	0.9856	0.8095	0.7538	0.8095	0.7519	0.8082
0.0008	13.0	8359	1.7113	0.8048	0.8076	0.8048	0.7753	0.7513	0.0175	0.0170	0.9739	0.9852	0.8048	0.7513	0.8048	0.7574	0.8046
0.0034	14.0	9002	1.6869	0.8087	0.8091	0.8087	0.7571	0.7590	0.0172	0.0166	0.9752	0.9856	0.8087	0.7590	0.8087	0.7567	0.8083
0.0023	15.0	9645	1.6877	0.8102	0.8108	0.8102	0.7633	0.7599	0.0170	0.0165	0.9750	0.9857	0.8102	0.7599	0.8102	0.7596	0.8098

Framework versions

Transformers 4.38.2
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.2

Task: Text Classification
Library: transformers
Type: bert
Created: Apr 11, 2024
Updated: Apr 13, 2024