bert-base-uncased-issues-128 – AI Model by Isaacp | AlphaNeural AI

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bert-base-uncased-issues-128

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bert-base-uncased-issues-128

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: 1.2456

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: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 16

Training results

Training Loss	Epoch	Step	Validation Loss
2.0986	1.0	291	1.6929
1.6401	2.0	582	1.4304
1.4881	3.0	873	1.3916
1.4	4.0	1164	1.3796
1.3416	5.0	1455	1.2012
1.2807	6.0	1746	1.2733
1.2396	7.0	2037	1.2646
1.1993	8.0	2328	1.2098
1.1661	9.0	2619	1.1862
1.1406	10.0	2910	1.2223
1.1294	11.0	3201	1.2056
1.1042	12.0	3492	1.1655
1.0827	13.0	3783	1.2525
1.0738	14.0	4074	1.1685
1.0626	15.0	4365	1.1182
1.0629	16.0	4656	1.2456

Framework versions

Transformers 4.11.3
Pytorch 1.13.0+cu116
Datasets 1.16.1
Tokenizers 0.10.3