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

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bert-base-uncased-issues-128

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google-bert/bert-base-uncased

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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: 1.2283

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 16

Training results

Training Loss	Epoch	Step	Validation Loss
2.0993	1.0	291	1.7072
1.6343	2.0	582	1.4999
1.4973	3.0	873	1.3487
1.3941	4.0	1164	1.3365
1.3301	5.0	1455	1.2322
1.2875	6.0	1746	1.3580
1.2324	7.0	2037	1.3062
1.2051	8.0	2328	1.3315
1.1638	9.0	2619	1.2213
1.141	10.0	2910	1.1727
1.1298	11.0	3201	1.1251
1.1116	12.0	3492	1.1758
1.086	13.0	3783	1.2267
1.0769	14.0	4074	1.2108
1.0725	15.0	4365	1.2226
1.0597	16.0	4656	1.2283

Framework versions

Transformers 4.49.0
Pytorch 2.7.0.dev20250218+cu128
Datasets 3.3.2
Tokenizers 0.21.0