mn-roberta-base-demo-named-entity – AI Model by 2rtl3 | AlphaNeural AI

You can deploy this model and start earning money today!

2rtl3/
mn-roberta-base-demo-named-entity

like

0

token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

mn-roberta-base-demo-named-entity

This model is a fine-tuned version of bayartsogt/mongolian-roberta-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1354
Precision: 0.9239
Recall: 0.9322
F1: 0.9280
Accuracy: 0.9797

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
0.1651	1.0	477	0.0835	0.8900	0.9145	0.9021	0.9745
0.0535	2.0	954	0.0780	0.9047	0.9243	0.9144	0.9775
0.0267	3.0	1431	0.0836	0.9184	0.9307	0.9245	0.9790
0.0159	4.0	1908	0.0936	0.9224	0.9329	0.9276	0.9803
0.0083	5.0	2385	0.1155	0.9224	0.9307	0.9265	0.9790
0.0055	6.0	2862	0.1211	0.9222	0.9316	0.9268	0.9793
0.0034	7.0	3339	0.1258	0.9199	0.9329	0.9263	0.9789
0.0025	8.0	3816	0.1300	0.9249	0.9339	0.9294	0.9799
0.002	9.0	4293	0.1352	0.9231	0.9313	0.9272	0.9795
0.0018	10.0	4770	0.1354	0.9239	0.9322	0.9280	0.9797

Framework versions

Transformers 4.28.0
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3