bert-base-uncased-issues-128 – AI Model by frahman | 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: 1.2551

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
2.0984	1.0	291	1.7081
1.6512	2.0	582	1.4289
1.4854	3.0	873	1.3845
1.3924	4.0	1164	1.3844
1.3375	5.0	1455	1.1944
1.2969	6.0	1746	1.2848
1.2443	7.0	2037	1.2678
1.1998	8.0	2328	1.2151
1.1805	9.0	2619	1.1638
1.1396	10.0	2910	1.2131
1.1333	11.0	3201	1.1966
1.0974	12.0	3492	1.1687
1.0822	13.0	3783	1.2283
1.0736	14.0	4074	1.1640
1.0595	15.0	4365	1.1207
1.0515	16.0	4656	1.2551

Framework versions

Transformers 4.17.0
Pytorch 1.10.0+cu111
Datasets 2.0.0
Tokenizers 0.11.6