legal-bert-lora-no-grad

xshubhamx/legal-bert-lora-no-grad

legal-bert-lora-no-grad is a machine learning model from xshubhamx. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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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Public

Updated Apr 19, 2024

Repo size

3.8 GB

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Public

Hugging Face

Repo makeup

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.safetensors3.2 GB · 83%

At a glance

License: cc-by-sa-4.0
Access: Public
Created: Apr 18, 2024
Updated: Apr 19, 2024
SHA: 466ecae5

Base models

nlpaueb/legal-bert-base-uncased

Model card

From the Hugging Face model README

legal-bert-lora-no-grad

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: 1.4787
Accuracy: 0.8273
Precision: 0.8270
Recall: 0.8273
Precision Macro: 0.7941
Recall Macro: 0.7774
Macro Fpr: 0.0157
Weighted Fpr: 0.0151
Weighted Specificity: 0.9767
Macro Specificity: 0.9867
Weighted Sensitivity: 0.8234
Macro Sensitivity: 0.7774
F1 Micro: 0.8234
F1 Macro: 0.7824
F1 Weighted: 0.8225

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: 30

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
1.5473	1.0	643	0.8485	0.7173	0.6897	0.7173	0.3892	0.4422	0.0278	0.0274	0.9658	0.9789	0.7173	0.4422	0.7173	0.3920	0.6869
0.7816	2.0	1286	0.7113	0.7545	0.7492	0.7545	0.5282	0.5054	0.0231	0.0227	0.9711	0.9817	0.7545	0.5054	0.7545	0.4751	0.7304
0.6956	3.0	1929	0.6460	0.7986	0.7793	0.7986	0.5436	0.5701	0.0184	0.0177	0.9741	0.9848	0.7986	0.5701	0.7986	0.5439	0.7833
0.4942	4.0	2572	0.6430	0.8110	0.8014	0.8110	0.6315	0.6670	0.0169	0.0164	0.9763	0.9858	0.8110	0.6670	0.8110	0.6413	0.8037
0.4088	5.0	3215	0.7148	0.8319	0.8301	0.8319	0.7951	0.7444	0.0150	0.0142	0.9758	0.9872	0.8319	0.7444	0.8319	0.7459	0.8254
0.3722	6.0	3858	0.7203	0.8319	0.8282	0.8319	0.7594	0.7604	0.0149	0.0142	0.9779	0.9873	0.8319	0.7604	0.8319	0.7582	0.8285
0.3088	7.0	4501	0.7796	0.8218	0.8283	0.8218	0.7927	0.7436	0.0158	0.0152	0.9765	0.9866	0.8218	0.7436	0.8218	0.7486	0.8203
0.245	8.0	5144	0.8732	0.8187	0.8171	0.8187	0.7696	0.7403	0.0163	0.0156	0.9752	0.9863	0.8187	0.7403	0.8187	0.7409	0.8135
0.2331	9.0	5787	0.8710	0.8265	0.8280	0.8265	0.7595	0.7521	0.0152	0.0148	0.9776	0.9869	0.8265	0.7521	0.8265	0.7530	0.8261
0.1878	10.0	6430	0.9866	0.8257	0.8261	0.8257	0.7672	0.7604	0.0153	0.0149	0.9788	0.9870	0.8257	0.7604	0.8257	0.7588	0.8240
0.1627	11.0	7073	1.0530	0.8257	0.8269	0.8257	0.7706	0.7711	0.0154	0.0149	0.9787	0.9870	0.8257	0.7711	0.8257	0.7675	0.8234
0.1301	12.0	7716	1.1042	0.8265	0.8246	0.8265	0.7633	0.7587	0.0155	0.0148	0.9763	0.9869	0.8265	0.7587	0.8265	0.7576	0.8228
0.1291	13.0	8359	1.1461	0.8234	0.8215	0.8234	0.7582	0.7613	0.0157	0.0151	0.9768	0.9867	0.8234	0.7613	0.8234	0.7581	0.8211
0.11	14.0	9002	1.1837	0.8226	0.8182	0.8226	0.7716	0.7576	0.0159	0.0152	0.9756	0.9865	0.8226	0.7576	0.8226	0.7627	0.8195
0.0863	15.0	9645	1.2020	0.8218	0.8185	0.8218	0.7616	0.7458	0.0160	0.0152	0.9754	0.9865	0.8218	0.7458	0.8218	0.7498	0.8183
0.0735	16.0	10288	1.2491	0.8187	0.8160	0.8187	0.7620	0.7464	0.0162	0.0156	0.9755	0.9863	0.8187	0.7464	0.8187	0.7517	0.8168
0.0802	17.0	10931	1.3288	0.8164	0.8165	0.8164	0.7471	0.7531	0.0164	0.0158	0.9765	0.9862	0.8164	0.7531	0.8164	0.7483	0.8152
0.0525	18.0	11574	1.3620	0.8133	0.8127	0.8133	0.7557	0.7478	0.0168	0.0161	0.9754	0.9859	0.8133	0.7478	0.8133	0.7486	0.8106
0.0474	19.0	12217	1.3783	0.8187	0.8220	0.8187	0.8154	0.7972	0.0162	0.0156	0.9755	0.9863	0.8187	0.7972	0.8187	0.8024	0.8187
0.0315	20.0	12860	1.4004	0.8226	0.8266	0.8226	0.8011	0.7910	0.0157	0.0152	0.9778	0.9867	0.8226	0.7910	0.8226	0.7907	0.8231
0.0325	21.0	13503	1.4683	0.8187	0.8198	0.8187	0.8030	0.7876	0.0161	0.0156	0.9765	0.9863	0.8187	0.7876	0.8187	0.7921	0.8182
0.0192	22.0	14146	1.4677	0.8249	0.8224	0.8249	0.7598	0.7482	0.0155	0.0149	0.9768	0.9868	0.8249	0.7482	0.8249	0.7505	0.8225
0.0235	23.0	14789	1.4610	0.8211	0.8221	0.8211	0.8090	0.7941	0.0160	0.0153	0.9765	0.9865	0.8211	0.7941	0.8211	0.7982	0.8200
0.0142	24.0	15432	1.4787	0.8273	0.8270	0.8273	0.8179	0.7977	0.0153	0.0147	0.9774	0.9870	0.8273	0.7977	0.8273	0.8054	0.8260
0.0172	25.0	16075	1.5374	0.8211	0.8231	0.8211	0.7830	0.7711	0.0159	0.0153	0.9767	0.9865	0.8211	0.7711	0.8211	0.7737	0.8212
0.0097	26.0	16718	1.5153	0.8242	0.8262	0.8242	0.8105	0.7894	0.0156	0.0150	0.9772	0.9868	0.8242	0.7894	0.8242	0.7954	0.8240
0.0109	27.0	17361	1.5565	0.8218	0.8237	0.8218	0.7876	0.7848	0.0158	0.0152	0.9770	0.9866	0.8218	0.7848	0.8218	0.7832	0.8214
0.0076	28.0	18004	1.5574	0.8226	0.8247	0.8226	0.7882	0.7843	0.0157	0.0152	0.9771	0.9867	0.8226	0.7843	0.8226	0.7836	0.8229
0.006	29.0	18647	1.5721	0.8234	0.8235	0.8234	0.7868	0.7771	0.0157	0.0151	0.9769	0.9867	0.8234	0.7771	0.8234	0.7788	0.8224
0.0035	30.0	19290	1.5803	0.8234	0.8234	0.8234	0.7941	0.7774	0.0157	0.0151	0.9767	0.9867	0.8234	0.7774	0.8234	0.7824	0.8225

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.1

License: cc-by-sa-4.0
Created: Apr 18, 2024
Updated: Apr 19, 2024