mongolian-roberta-base – AI Model by Dakie | AlphaNeural AI

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Dakie/
mongolian-roberta-base

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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mongolian-roberta-base

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: 0.1308
Precision: 0.9243
Recall: 0.9322
F1: 0.9283
Accuracy: 0.9799

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: 9

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1632	1.0	477	0.0908	0.8293	0.8817	0.8547	0.9682
0.0607	2.0	954	0.0920	0.8506	0.8898	0.8698	0.9712
0.0331	3.0	1431	0.0975	0.9192	0.9267	0.9229	0.9779
0.0148	4.0	1908	0.1024	0.9179	0.9294	0.9236	0.9786
0.0087	5.0	2385	0.1091	0.9196	0.9296	0.9246	0.9796
0.0052	6.0	2862	0.1222	0.9240	0.9323	0.9281	0.9794
0.0033	7.0	3339	0.1233	0.9214	0.9317	0.9265	0.9796
0.0024	8.0	3816	0.1310	0.9250	0.9315	0.9282	0.9797
0.0016	9.0	4293	0.1308	0.9243	0.9322	0.9283	0.9799

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3