mongolian-gpt2-ner – AI Model by Enkhbold | AlphaNeural AI

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Enkhbold/
mongolian-gpt2-ner

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token-classification

generated_from_trainer

autotrain_compatible

text-generation-inference

endpoints_compatible

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mongolian-gpt2-ner

This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2599
Precision: 0.1483
Recall: 0.2561
F1: 0.1878
Accuracy: 0.9149

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
0.4822	1.0	477	0.3452	0.1156	0.2072	0.1484	0.8876
0.3376	2.0	954	0.3196	0.1369	0.2304	0.1717	0.8975
0.3084	3.0	1431	0.2915	0.1242	0.2257	0.1603	0.9015
0.2889	4.0	1908	0.2800	0.1328	0.2375	0.1704	0.9063
0.275	5.0	2385	0.2734	0.1439	0.2452	0.1814	0.9099
0.264	6.0	2862	0.2691	0.1426	0.2420	0.1795	0.9115
0.256	7.0	3339	0.2639	0.1411	0.2442	0.1789	0.9129
0.2498	8.0	3816	0.2628	0.1482	0.2511	0.1864	0.9135
0.2438	9.0	4293	0.2603	0.1483	0.2548	0.1875	0.9143
0.2388	10.0	4770	0.2599	0.1483	0.2561	0.1878	0.9149

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3