bert-base-uncased-issues-128 – AI Model by Shenghao1993 | AlphaNeural AI

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Shenghao1993/
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: 1.2503

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
2.0976	1.0	291	1.7064
1.6388	2.0	582	1.4335
1.4846	3.0	873	1.3750
1.4003	4.0	1164	1.3749
1.3393	5.0	1455	1.1970
1.2848	6.0	1746	1.2826
1.2385	7.0	2037	1.2652
1.1974	8.0	2328	1.2158
1.1653	9.0	2619	1.1808
1.142	10.0	2910	1.2091
1.13	11.0	3201	1.2147
1.1051	12.0	3492	1.1668
1.0802	13.0	3783	1.2550
1.0781	14.0	4074	1.1659
1.0644	15.0	4365	1.1272
1.0618	16.0	4656	1.2503

Framework versions

Transformers 4.21.1
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1