metadata

tags:
  - generated_from_trainer
datasets:
  - wikiann
metrics:
  - precision
  - recall
  - f1
  - accuracy
model_index:
  - name: bert-srb-ner
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: wikiann
          type: wikiann
          args: sr
        metric:
          name: Accuracy
          type: accuracy
          value: 0.9546696220907545

bert-srb-ner

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

Loss: 0.3561
Precision: 0.8909
Recall: 0.9082
F1: 0.8995
Accuracy: 0.9547

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
0.3907	1.0	625	0.2316	0.8255	0.8314	0.8285	0.9259
0.2091	2.0	1250	0.1920	0.8598	0.8731	0.8664	0.9420
0.1562	3.0	1875	0.1833	0.8608	0.8820	0.8713	0.9441
0.0919	4.0	2500	0.1985	0.8712	0.8886	0.8798	0.9476
0.0625	5.0	3125	0.2195	0.8762	0.8923	0.8842	0.9485
0.0545	6.0	3750	0.2320	0.8706	0.9004	0.8852	0.9495
0.0403	7.0	4375	0.2459	0.8817	0.8957	0.8887	0.9505
0.0269	8.0	5000	0.2603	0.8813	0.9021	0.8916	0.9516
0.0193	9.0	5625	0.2916	0.8812	0.8949	0.8880	0.9500
0.0162	10.0	6250	0.2938	0.8814	0.9025	0.8918	0.9520
0.0134	11.0	6875	0.3330	0.8809	0.8961	0.8885	0.9497
0.0076	12.0	7500	0.3141	0.8840	0.9025	0.8932	0.9524
0.0069	13.0	8125	0.3292	0.8819	0.9065	0.8940	0.9535
0.0053	14.0	8750	0.3454	0.8844	0.9018	0.8930	0.9523
0.0038	15.0	9375	0.3519	0.8912	0.9061	0.8986	0.9539
0.0034	16.0	10000	0.3437	0.8894	0.9038	0.8965	0.9539
0.0024	17.0	10625	0.3518	0.8896	0.9072	0.8983	0.9543
0.0018	18.0	11250	0.3572	0.8877	0.9072	0.8973	0.9543
0.0015	19.0	11875	0.3554	0.8910	0.9081	0.8994	0.9549
0.0011	20.0	12500	0.3561	0.8909	0.9082	0.8995	0.9547

Framework versions

Transformers 4.9.2
Pytorch 1.9.0
Datasets 1.11.0
Tokenizers 0.10.1