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

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MunSu/
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: 1.2529

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
2.1006	1.0	291	1.7028
1.653	2.0	582	1.4206
1.486	3.0	873	1.3993
1.396	4.0	1164	1.3890
1.3329	5.0	1455	1.1999
1.2962	6.0	1746	1.2835
1.2454	7.0	2037	1.2793
1.2014	8.0	2328	1.2005
1.183	9.0	2619	1.1730
1.1396	10.0	2910	1.2259
1.1327	11.0	3201	1.1999
1.0988	12.0	3492	1.1731
1.0813	13.0	3783	1.2428
1.0744	14.0	4074	1.1532
1.0608	15.0	4365	1.1236
1.0532	16.0	4656	1.2529

Framework versions

Transformers 4.26.1
Pytorch 1.9.0+cu111
Datasets 2.10.1
Tokenizers 0.13.2