sequence-ranker-for-dbpedia-ontology – AI Model by IvAnastasia | AlphaNeural AI

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IvAnastasia/
sequence-ranker-for-dbpedia-ontology

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text-classification

generated_from_trainer

google-bert/bert-base-cased

autotrain_compatible

endpoints_compatible

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test_trainer

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

Loss: 1.0633
F1: 0.3413
Precision: 0.2765
Recall: 0.4456
Accuracy: 0.7017

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: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Precision	Recall	Accuracy
0.6981	1.0	285	0.6720	0.3035	0.2919	0.3161	0.7484
0.6726	2.0	570	0.6554	0.3547	0.2740	0.5026	0.6828
0.6402	3.0	855	0.6574	0.3609	0.2675	0.5544	0.6595
0.568	4.0	1140	0.7293	0.3620	0.3154	0.4249	0.7403
0.4926	5.0	1425	0.8515	0.3383	0.2883	0.4093	0.7224
0.4303	6.0	1710	0.9507	0.3538	0.2813	0.4767	0.6981
0.38	7.0	1995	1.0129	0.3366	0.2685	0.4508	0.6918
0.3437	8.0	2280	1.0633	0.3413	0.2765	0.4456	0.7017

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2