mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_128

gokuls/mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_128

mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_128 is a text classification model from gokuls. 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: mobilebert
Access: Public
Created: Feb 2, 2023
Updated: Feb 2, 2023
SHA: a7ac9016

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Datasets

glue

Model card

From the Hugging Face model README

mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_128

This model is a fine-tuned version of google/mobilebert-uncased on the GLUE MRPC dataset. It achieves the following results on the evaluation set:

Loss: 0.1262
Accuracy: 0.9877
F1: 0.9911
Combined Score: 0.9894

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: 128
eval_batch_size: 128
seed: 10
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Combined Score
0.3021	1.0	1959	0.2407	0.9510	0.9636	0.9573
0.2326	2.0	3918	0.2009	0.9779	0.9841	0.9810
0.224	3.0	5877	0.1790	0.9730	0.9807	0.9769
0.219	4.0	7836	0.1789	0.9804	0.9859	0.9831
0.2153	5.0	9795	0.1804	0.9804	0.9859	0.9831
0.2121	6.0	11754	0.1754	0.9755	0.9824	0.9789
0.2088	7.0	13713	0.1661	0.9804	0.9859	0.9831
0.2056	8.0	15672	0.1654	0.9779	0.9841	0.9810
0.2031	9.0	17631	0.1714	0.9828	0.9876	0.9852
0.2012	10.0	19590	0.1617	0.9828	0.9876	0.9852
0.1993	11.0	21549	0.1610	0.9828	0.9876	0.9852
0.1978	12.0	23508	0.1507	0.9853	0.9894	0.9873
0.1964	13.0	25467	0.1496	0.9902	0.9929	0.9915
0.1953	14.0	27426	0.1569	0.9828	0.9876	0.9852
0.1943	15.0	29385	0.1524	0.9877	0.9911	0.9894
0.1934	16.0	31344	0.1492	0.9877	0.9911	0.9894
0.1926	17.0	33303	0.1480	0.9902	0.9929	0.9915
0.1918	18.0	35262	0.1416	0.9828	0.9876	0.9852
0.1912	19.0	37221	0.1420	0.9853	0.9894	0.9873
0.1905	20.0	39180	0.1396	0.9853	0.9894	0.9873
0.1899	21.0	41139	0.1458	0.9853	0.9894	0.9873
0.1893	22.0	43098	0.1484	0.9877	0.9911	0.9894
0.1888	23.0	45057	0.1407	0.9877	0.9911	0.9894
0.1883	24.0	47016	0.1372	0.9804	0.9858	0.9831
0.1878	25.0	48975	0.1354	0.9877	0.9911	0.9894
0.1873	26.0	50934	0.1368	0.9902	0.9929	0.9915
0.1869	27.0	52893	0.1378	0.9926	0.9947	0.9936
0.1865	28.0	54852	0.1381	0.9853	0.9894	0.9873
0.1861	29.0	56811	0.1329	0.9877	0.9911	0.9894
0.1857	30.0	58770	0.1342	0.9902	0.9929	0.9915
0.1854	31.0	60729	0.1346	0.9902	0.9929	0.9915
0.1849	32.0	62688	0.1323	0.9902	0.9929	0.9915
0.1846	33.0	64647	0.1317	0.9877	0.9911	0.9894
0.1843	34.0	66606	0.1318	0.9877	0.9911	0.9894
0.1839	35.0	68565	0.1311	0.9926	0.9947	0.9936
0.1837	36.0	70524	0.1291	0.9877	0.9911	0.9894
0.1834	37.0	72483	0.1313	0.9853	0.9893	0.9873
0.1831	38.0	74442	0.1262	0.9877	0.9911	0.9894
0.1828	39.0	76401	0.1288	0.9877	0.9911	0.9894
0.1825	40.0	78360	0.1295	0.9926	0.9947	0.9936
0.1823	41.0	80319	0.1277	0.9902	0.9929	0.9915
0.182	42.0	82278	0.1265	0.9902	0.9929	0.9915
0.1818	43.0	84237	0.1273	0.9902	0.9929	0.9915

Framework versions

Transformers 4.26.0
Pytorch 1.14.0a0+410ce96
Datasets 2.9.0
Tokenizers 0.13.2

Task: Text Classification
Library: transformers
Type: mobilebert
License: apache-2.0
Languages: en
Created: Feb 2, 2023
Updated: Feb 2, 2023