legal-bert-base-uncased

xshubhamx/legal-bert-base-uncased

legal-bert-base-uncased 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. The card lists the license as cc-by-sa-4.0.

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

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At a glance

Task: Text Classification
Library: transformers
License: cc-by-sa-4.0
Model type: bert
Access: Public
Created: Apr 12, 2024
Updated: Apr 14, 2024
SHA: b475be24

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Base models

nlpaueb/legal-bert-base-uncased

Model card

From the Hugging Face model README

legal-bert-base-uncased

This model is a fine-tuned version of nlpaueb/legal-bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.1536
Accuracy: 0.8203
Precision: 0.8212
Recall: 0.8203
Precision Macro: 0.7660
Recall Macro: 0.7548
Macro Fpr: 0.0156
Weighted Fpr: 0.0150
Weighted Specificity: 0.9766
Macro Specificity: 0.9867
Weighted Sensitivity: 0.8242
Macro Sensitivity: 0.7548
F1 Micro: 0.8242
F1 Macro: 0.7566
F1 Weighted: 0.8221

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
1.1096	1.0	643	0.6748	0.7978	0.7855	0.7978	0.6239	0.6340	0.0188	0.0178	0.9702	0.9845	0.7978	0.6340	0.7978	0.6134	0.7840
0.6187	2.0	1286	0.6449	0.8110	0.8196	0.8110	0.7806	0.7327	0.0169	0.0164	0.9755	0.9858	0.8110	0.7327	0.8110	0.7268	0.8090
0.4747	3.0	1929	0.8151	0.8149	0.8192	0.8149	0.7659	0.7390	0.0166	0.0160	0.9761	0.9861	0.8149	0.7390	0.8149	0.7370	0.8125
0.2645	4.0	2572	0.9345	0.8218	0.8198	0.8218	0.7446	0.7413	0.0158	0.0152	0.9774	0.9866	0.8218	0.7413	0.8218	0.7385	0.8189
0.1901	5.0	3215	1.0929	0.8195	0.8242	0.8195	0.8264	0.7432	0.0161	0.0155	0.9750	0.9863	0.8195	0.7432	0.8195	0.7595	0.8166
0.1131	6.0	3858	1.1536	0.8203	0.8212	0.8203	0.7968	0.7786	0.0159	0.0154	0.9766	0.9865	0.8203	0.7786	0.8203	0.7840	0.8197
0.063	7.0	4501	1.3218	0.8118	0.8184	0.8118	0.7518	0.7526	0.0166	0.0163	0.9773	0.9859	0.8118	0.7526	0.8118	0.7495	0.8136
0.0264	8.0	5144	1.3863	0.8257	0.8262	0.8257	0.7784	0.7768	0.0155	0.0149	0.9768	0.9868	0.8257	0.7768	0.8257	0.7730	0.8247
0.03	9.0	5787	1.5542	0.8079	0.8167	0.8079	0.7639	0.7653	0.0172	0.0167	0.9744	0.9855	0.8079	0.7653	0.8079	0.7595	0.8096
0.0149	10.0	6430	1.5835	0.8141	0.8155	0.8141	0.7545	0.7361	0.0168	0.0160	0.9730	0.9858	0.8141	0.7361	0.8141	0.7412	0.8127
0.005	11.0	7073	1.5325	0.8242	0.8250	0.8242	0.7805	0.7812	0.0156	0.0150	0.9758	0.9867	0.8242	0.7812	0.8242	0.7681	0.8226
0.003	12.0	7716	1.5714	0.8288	0.8299	0.8288	0.7701	0.7679	0.0152	0.0145	0.9765	0.9870	0.8288	0.7679	0.8288	0.7626	0.8276
0.0033	13.0	8359	1.5511	0.8249	0.8219	0.8249	0.7676	0.7598	0.0156	0.0149	0.9760	0.9867	0.8249	0.7598	0.8249	0.7608	0.8225
0.0018	14.0	9002	1.5510	0.8249	0.8225	0.8249	0.7686	0.7554	0.0155	0.0149	0.9767	0.9868	0.8249	0.7554	0.8249	0.7572	0.8224
0.0008	15.0	9645	1.5469	0.8242	0.8220	0.8242	0.7660	0.7548	0.0156	0.0150	0.9766	0.9867	0.8242	0.7548	0.8242	0.7566	0.8221

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
License: cc-by-sa-4.0
Created: Apr 12, 2024
Updated: Apr 14, 2024