mongolian-xlm-roberta-large-ner – AI Model by srglnjmb | AlphaNeural AI

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srglnjmb/
mongolian-xlm-roberta-large-ner

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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mongolian-xlm-roberta-large-ner

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

Loss: 0.1256
Precision: 0.9361
Recall: 0.9423
F1: 0.9392
Accuracy: 0.9824

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
0.1837	1.0	477	0.0939	0.8524	0.8895	0.8705	0.9745
0.0736	2.0	954	0.0731	0.9318	0.9370	0.9344	0.9809
0.0525	3.0	1431	0.0724	0.9244	0.9311	0.9278	0.9795
0.036	4.0	1908	0.0807	0.9312	0.9409	0.9361	0.9819
0.0248	5.0	2385	0.0855	0.9314	0.9407	0.9360	0.9814
0.0163	6.0	2862	0.1014	0.9327	0.9397	0.9362	0.9815
0.0112	7.0	3339	0.0997	0.9354	0.9433	0.9393	0.9822
0.0064	8.0	3816	0.1171	0.9384	0.9432	0.9408	0.9824
0.0049	9.0	4293	0.1237	0.9355	0.9418	0.9387	0.9822
0.0024	10.0	4770	0.1256	0.9361	0.9423	0.9392	0.9824

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3