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nemuwn/
Mongolian-distilbert-base-multilingual-cased-ner

Name: Mongolian-distilbert-base-multilingual-cased-ner
Availability: InStock

generated_from_trainer

apache-2.0

autotrain_compatible

endpoints_compatible

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Mongolian-distilbert-base-multilingual-cased-ner

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

Loss: 0.1344
Precision: 0.8878
Recall: 0.9055
F1: 0.8966
Accuracy: 0.9739

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
0.2155	1.0	477	0.1297	0.8050	0.8476	0.8257	0.9584
0.1037	2.0	954	0.0951	0.8505	0.8882	0.8690	0.9699
0.0687	3.0	1431	0.0978	0.8686	0.8924	0.8803	0.9711
0.05	4.0	1908	0.1087	0.8764	0.8955	0.8858	0.9719
0.0343	5.0	2385	0.1109	0.8781	0.8992	0.8885	0.9729
0.0264	6.0	2862	0.1169	0.8798	0.9011	0.8903	0.9729
0.0182	7.0	3339	0.1221	0.8871	0.9051	0.8960	0.9744
0.0146	8.0	3816	0.1286	0.8846	0.9036	0.8940	0.9735
0.0109	9.0	4293	0.1347	0.8880	0.9046	0.8962	0.9737
0.0095	10.0	4770	0.1344	0.8878	0.9055	0.8966	0.9739

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3

nemuwn/Mongolian-distilbert-base-multilingual-cased-ner

Mongolian-distilbert-base-multilingual-cased-ner

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

nemuwn/
Mongolian-distilbert-base-multilingual-cased-ner