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fabriceyhc/bert-base-uncased-yahoo_answers_topics

sourceHugging Faceapache-2.0updated 5y agoView on Hugging Face

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bert-base-uncased-yahooanswerstopics

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

—Loss: 0.8092
—Accuracy: 0.7499

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
—trainbatchsize: 8
—evalbatchsize: 16
—seed: 42
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—lrschedulerwarmup_steps: 86625
—training_steps: 866250

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.162	0.01	2000	1.7444	0.5681
1.3126	0.02	4000	1.0081	0.7054
0.9592	0.03	6000	0.9021	0.7234
0.8903	0.05	8000	0.8827	0.7276
0.8685	0.06	10000	0.8540	0.7341
0.8422	0.07	12000	0.8547	0.7365
0.8535	0.08	14000	0.8264	0.7372
0.8178	0.09	16000	0.8331	0.7389
0.8325	0.1	18000	0.8242	0.7411
0.8181	0.12	20000	0.8356	0.7437
0.8171	0.13	22000	0.8090	0.7451
0.8092	0.14	24000	0.8469	0.7392
0.8057	0.15	26000	0.8185	0.7478
0.8085	0.16	28000	0.8090	0.7467
0.8229	0.17	30000	0.8225	0.7417
0.8151	0.18	32000	0.8262	0.7419
0.81	0.2	34000	0.8149	0.7383
0.8073	0.21	36000	0.8225	0.7441
0.816	0.22	38000	0.8037	0.744
0.8217	0.23	40000	0.8409	0.743
0.82	0.24	42000	0.8286	0.7385
0.8101	0.25	44000	0.8282	0.7413
0.8254	0.27	46000	0.8170	0.7414

Framework versions

—Transformers 4.10.2
—Pytorch 1.7.1
—Datasets 1.6.1
—Tokenizers 0.10.3