mongolian-roberta-large-mnli-ner – AI Model by Blgn94 | AlphaNeural AI

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Blgn94/
mongolian-roberta-large-mnli-ner

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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mongolian-roberta-large-mnli-ner

This model is a fine-tuned version of roberta-large-mnli on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1941
Precision: 0.7734
Recall: 0.8488
F1: 0.8094
Accuracy: 0.9582

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
0.3433	1.0	477	0.2252	0.6196	0.7338	0.6719	0.9288
0.2067	2.0	954	0.1859	0.6981	0.7908	0.7416	0.9381
0.165	3.0	1431	0.1776	0.7308	0.8112	0.7689	0.9455
0.1362	4.0	1908	0.1639	0.7513	0.8265	0.7871	0.9520
0.109	5.0	2385	0.1703	0.7524	0.8302	0.7894	0.9517
0.0873	6.0	2862	0.1690	0.7643	0.8396	0.8002	0.9552
0.0697	7.0	3339	0.1754	0.7696	0.8442	0.8052	0.9557
0.0552	8.0	3816	0.1793	0.7687	0.8468	0.8059	0.9572
0.0434	9.0	4293	0.1878	0.7842	0.8507	0.8161	0.9580
0.0354	10.0	4770	0.1941	0.7734	0.8488	0.8094	0.9582

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3