SingSeqBERT-UCIRetail – AI Model by MSParkDev | AlphaNeural AI

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MSParkDev/
SingSeqBERT-UCIRetail

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text-classification

generated_from_trainer

google-bert/bert-base-multilingual-cased

autotrain_compatible

endpoints_compatible

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SingSeqBERT-UCIRetail

This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4882
Accuracy: 0.7685
F1: 0.7672

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: 8
eval_batch_size: 8
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	Accuracy	F1
No log	1.0	456	0.5482	0.7479	0.7425
0.6336	2.0	912	0.5108	0.7570	0.7569
0.5437	3.0	1368	0.4882	0.7685	0.7672
0.4872	4.0	1824	0.5918	0.7825	0.7825
0.4329	5.0	2280	0.6156	0.7652	0.7652
0.3957	6.0	2736	0.6598	0.7685	0.7683
0.3439	7.0	3192	0.7881	0.7768	0.7756
0.3068	8.0	3648	0.9189	0.7545	0.7536
0.2635	9.0	4104	1.0319	0.7619	0.7619
0.2305	10.0	4560	1.0976	0.7586	0.7586

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.0.0
Datasets 2.14.5
Tokenizers 0.14.1