metadata

tags:
  - generated_from_trainer
datasets:
  - wikiann
metrics:
  - precision
  - recall
  - f1
  - accuracy
model_index:
  - name: electra-srb-ner
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: wikiann
          type: wikiann
          args: sr
        metric:
          name: Accuracy
          type: accuracy
          value: 0.9568394937134688

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