starclass_bert – AI Model by dnttestmee | AlphaNeural AI

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dnttestmee/
starclass_bert

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google-bert/bert-base-uncased

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starclass_bert

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

Loss: 0.1168
Accuracy: 0.9683
Precision: 0.9718
Recall: 0.9683
F1: 0.9683

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: 5e-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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.2759	1.0	16	0.7935	0.9048	0.9073	0.9048	0.9043
0.5557	2.0	32	0.3849	0.9048	0.9133	0.9048	0.9029
0.3352	3.0	48	0.1927	0.9365	0.9418	0.9365	0.9372
0.1037	4.0	64	0.1253	0.9683	0.9718	0.9683	0.9683
0.0465	5.0	80	0.1168	0.9683	0.9718	0.9683	0.9683

Framework versions

Transformers 4.36.2
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.15.2