metadata

language:
  - mn
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: mongolian-Davlan-distilbert-base-multilingual-cased-ner-hrl
    results: []

mongolian-Davlan-distilbert-base-multilingual-cased-ner-hrl

This model is a fine-tuned version of Davlan/distilbert-base-multilingual-cased-ner-hrl on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1589
Precision: 0.8750
Recall: 0.8977
F1: 0.8862
Accuracy: 0.9714

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: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1974	1.0	477	0.1235	0.8022	0.8510	0.8259	0.9600
0.0953	2.0	954	0.1128	0.8315	0.8697	0.8502	0.9641
0.0621	3.0	1431	0.1149	0.8537	0.8832	0.8682	0.9675
0.0414	4.0	1908	0.1245	0.8534	0.8842	0.8686	0.9676
0.0289	5.0	2385	0.1400	0.8630	0.8895	0.8760	0.9692
0.0214	6.0	2862	0.1448	0.8612	0.8908	0.8758	0.9693
0.0156	7.0	3339	0.1534	0.8664	0.8924	0.8792	0.9699
0.0114	8.0	3816	0.1568	0.8755	0.8957	0.8855	0.9711
0.009	9.0	4293	0.1580	0.8710	0.8953	0.8830	0.9713
0.0076	10.0	4770	0.1589	0.8750	0.8977	0.8862	0.9714

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3