electra-srb-ner

This model was trained from scratch on the wikiann dataset. It achieves the following results on the evaluation set:

• Loss: 0.3406
• Precision: 0.8934
• Recall: 0.9087
• F1: 0.9010
• Accuracy: 0.9568

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: 2e-05
• train_batch_size: 32
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.3686	1.0	625	0.2108	0.8326	0.8494	0.8409	0.9335
0.1886	2.0	1250	0.1784	0.8737	0.8713	0.8725	0.9456
0.1323	3.0	1875	0.1805	0.8654	0.8870	0.8760	0.9468
0.0675	4.0	2500	0.2018	0.8736	0.8880	0.8807	0.9502
0.0425	5.0	3125	0.2162	0.8818	0.8945	0.8881	0.9512
0.0343	6.0	3750	0.2492	0.8790	0.8928	0.8859	0.9513
0.0253	7.0	4375	0.2562	0.8821	0.9006	0.8912	0.9525
0.0142	8.0	5000	0.2788	0.8807	0.9013	0.8909	0.9524
0.0114	9.0	5625	0.2793	0.8861	0.9002	0.8931	0.9534
0.0095	10.0	6250	0.2967	0.8887	0.9034	0.8960	0.9550
0.008	11.0	6875	0.2993	0.8899	0.9067	0.8982	0.9556
0.0048	12.0	7500	0.3215	0.8887	0.9038	0.8962	0.9545
0.0034	13.0	8125	0.3242	0.8897	0.9068	0.8982	0.9554
0.003	14.0	8750	0.3311	0.8884	0.9085	0.8983	0.9559
0.0025	15.0	9375	0.3383	0.8943	0.9062	0.9002	0.9562
0.0011	16.0	10000	0.3346	0.8941	0.9112	0.9026	0.9574
0.0015	17.0	10625	0.3362	0.8944	0.9081	0.9012	0.9567
0.001	18.0	11250	0.3464	0.8877	0.9100	0.8987	0.9559
0.0012	19.0	11875	0.3415	0.8944	0.9089	0.9016	0.9568
0.0005	20.0	12500	0.3406	0.8934	0.9087	0.9010	0.9568

Framework versions

• Transformers 4.9.2
• Pytorch 1.9.0
• Datasets 1.11.0
• Tokenizers 0.10.1