case-analysis-bert-base-uncased

cite-text-analysis/case-analysis-bert-base-uncased

case-analysis-bert-base-uncased is a text classification model from cite-text-analysis. 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.

- loss: 1.7243 - accuracy: 0.7996 - precision: 0.7969 - recall: 0.7996 - precisionmacro: 0.6535 - recallmacro: 0.6526 - macrofpr: 0.0942 - weightedfpr: 0.0771 - weightedspecificity: 0.8638 - macrospecificity: 0.9158 -…

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: May 9, 2024
Updated: May 9, 2024
SHA: 0e8c745e

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Base models

google-bert/bert-base-uncased

Model card

From the Hugging Face model README

Metrics

loss: 1.7243
accuracy: 0.7996
precision: 0.7969
recall: 0.7996
precision_macro: 0.6535
recall_macro: 0.6526
macro_fpr: 0.0942
weighted_fpr: 0.0771
weighted_specificity: 0.8638
macro_specificity: 0.9158
weighted_sensitivity: 0.7996
macro_sensitivity: 0.6526
f1_micro: 0.7996
f1_macro: 0.6529
f1_weighted: 0.7982
runtime: 351.9249
samples_per_second: 1.2760
steps_per_second: 0.1620

case-analysis-bert-base-uncased

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

Loss: 1.7243
Accuracy: 0.7996
Precision: 0.7969
Recall: 0.7996
Precision Macro: 0.6427
Recall Macro: 0.6184
Macro Fpr: 0.0946
Weighted Fpr: 0.0712
Weighted Specificity: 0.8449
Macro Specificity: 0.9145
Weighted Sensitivity: 0.8129
Macro Sensitivity: 0.6184
F1 Micro: 0.8129
F1 Macro: 0.6284
F1 Weighted: 0.8035

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
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
No log	1.0	224	0.7283	0.7862	0.7487	0.7862	0.5848	0.5572	0.1142	0.0831	0.8036	0.8974	0.7862	0.5572	0.7862	0.5606	0.7597
No log	2.0	448	0.8160	0.7996	0.7603	0.7996	0.5770	0.6065	0.0997	0.0771	0.8417	0.9103	0.7996	0.6065	0.7996	0.5914	0.7794
0.6512	3.0	672	0.8588	0.7906	0.7598	0.7906	0.5770	0.5989	0.1005	0.0811	0.8512	0.9105	0.7906	0.5989	0.7906	0.5840	0.7720
0.6512	4.0	896	1.0821	0.7817	0.7819	0.7817	0.6214	0.6429	0.0996	0.0851	0.8679	0.9124	0.7817	0.6429	0.7817	0.6299	0.7805
0.3466	5.0	1120	1.0612	0.8085	0.7999	0.8085	0.7129	0.6263	0.0948	0.0732	0.8470	0.9139	0.8085	0.6263	0.8085	0.6195	0.7928
0.3466	6.0	1344	1.2559	0.7929	0.7877	0.7929	0.6206	0.6362	0.0951	0.0801	0.8717	0.9161	0.7929	0.6362	0.7929	0.6273	0.7897
0.1715	7.0	1568	1.3701	0.7929	0.7889	0.7929	0.6345	0.6179	0.0991	0.0801	0.8558	0.9122	0.7929	0.6179	0.7929	0.6237	0.7893
0.1715	8.0	1792	1.4005	0.8107	0.8035	0.8107	0.6578	0.6370	0.0922	0.0722	0.8607	0.9179	0.8107	0.6370	0.8107	0.6464	0.8064
0.0636	9.0	2016	1.4737	0.8018	0.7881	0.8018	0.6583	0.6149	0.1026	0.0761	0.8271	0.9072	0.8018	0.6149	0.8018	0.6263	0.7896
0.0636	10.0	2240	1.7569	0.7884	0.7962	0.7884	0.6275	0.6428	0.0960	0.0821	0.8750	0.9158	0.7884	0.6428	0.7884	0.6332	0.7909
0.0636	11.0	2464	1.7141	0.7906	0.7824	0.7906	0.6166	0.6083	0.1035	0.0811	0.8424	0.9083	0.7906	0.6083	0.7906	0.6101	0.7845
0.0159	12.0	2688	1.7144	0.7951	0.7914	0.7951	0.6393	0.6413	0.0969	0.0791	0.8610	0.9140	0.7951	0.6413	0.7951	0.6373	0.7917
0.0159	13.0	2912	1.7243	0.7996	0.7969	0.7996	0.6535	0.6526	0.0942	0.0771	0.8638	0.9158	0.7996	0.6526	0.7996	0.6529	0.7982
0.0043	14.0	3136	1.8551	0.7973	0.7948	0.7973	0.6576	0.6189	0.1041	0.0781	0.8314	0.9072	0.7973	0.6189	0.7973	0.6335	0.7912
0.0043	15.0	3360	1.8841	0.7929	0.7869	0.7929	0.6154	0.6162	0.1008	0.0801	0.8511	0.9110	0.7929	0.6162	0.7929	0.6104	0.7861
0.0029	16.0	3584	2.0853	0.7550	0.7837	0.7550	0.6010	0.6119	0.1100	0.0976	0.8698	0.9062	0.7550	0.6119	0.7550	0.6015	0.7661
0.0029	17.0	3808	1.9722	0.7840	0.7783	0.7840	0.6018	0.5839	0.1076	0.0841	0.8394	0.9059	0.7840	0.5839	0.7840	0.5917	0.7797
0.0071	18.0	4032	1.8735	0.7996	0.7783	0.7996	0.6086	0.5917	0.1053	0.0771	0.8193	0.9047	0.7996	0.5917	0.7996	0.5960	0.7840
0.0071	19.0	4256	1.8294	0.8018	0.7840	0.8018	0.6114	0.5943	0.1025	0.0761	0.8308	0.9082	0.8018	0.5943	0.8018	0.6001	0.7895
0.0071	20.0	4480	1.8578	0.7973	0.7939	0.7973	0.6367	0.6232	0.0990	0.0781	0.8497	0.9118	0.7973	0.6232	0.7973	0.6285	0.7942
0.0049	21.0	4704	1.8770	0.7973	0.7939	0.7973	0.6367	0.6232	0.0990	0.0781	0.8497	0.9118	0.7973	0.6232	0.7973	0.6285	0.7942
0.0049	22.0	4928	1.8932	0.7951	0.7876	0.7951	0.6219	0.6119	0.1007	0.0791	0.8461	0.9103	0.7951	0.6119	0.7951	0.6155	0.7900
0.0015	23.0	5152	1.9834	0.7996	0.7965	0.7996	0.6441	0.6389	0.0960	0.0771	0.8599	0.9149	0.7996	0.6389	0.7996	0.6403	0.7971
0.0015	24.0	5376	1.9926	0.8018	0.7984	0.8018	0.6468	0.6399	0.0952	0.0761	0.8603	0.9155	0.8018	0.6399	0.8018	0.6422	0.7991
0.0001	25.0	5600	1.9771	0.7973	0.7790	0.7973	0.6025	0.6024	0.1011	0.0781	0.8420	0.9098	0.7973	0.6024	0.7973	0.6017	0.7871
0.0001	26.0	5824	1.9871	0.7951	0.7770	0.7951	0.5996	0.6015	0.1020	0.0791	0.8416	0.9092	0.7951	0.6015	0.7951	0.5997	0.7850
0.0	27.0	6048	1.8756	0.8129	0.7961	0.8129	0.6440	0.6200	0.0939	0.0712	0.8462	0.9148	0.8129	0.6200	0.8129	0.6293	0.8029
0.0	28.0	6272	1.8473	0.8151	0.7998	0.8151	0.6463	0.6194	0.0937	0.0703	0.8453	0.9151	0.8151	0.6194	0.8151	0.6305	0.8056
0.0	29.0	6496	1.8525	0.8129	0.7975	0.8129	0.6427	0.6184	0.0946	0.0712	0.8449	0.9145	0.8129	0.6184	0.8129	0.6284	0.8035
0.0001	30.0	6720	1.8540	0.8129	0.7975	0.8129	0.6427	0.6184	0.0946	0.0712	0.8449	0.9145	0.8129	0.6184	0.8129	0.6284	0.8035

Framework versions

Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: May 9, 2024
Updated: May 9, 2024