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

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Hanwoon/
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: 1.2449

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
2.099	1.0	291	1.6946
1.6396	2.0	582	1.4288
1.4875	3.0	873	1.3893
1.399	4.0	1164	1.3812
1.341	5.0	1455	1.2004
1.2803	6.0	1746	1.2738
1.2397	7.0	2037	1.2645
1.199	8.0	2328	1.2092
1.166	9.0	2619	1.1871
1.1406	10.0	2910	1.2244
1.1293	11.0	3201	1.2061
1.1037	12.0	3492	1.1621
1.0824	13.0	3783	1.2540
1.0738	14.0	4074	1.1703
1.0625	15.0	4365	1.1195
1.0628	16.0	4656	1.2449

Framework versions

Transformers 4.23.1
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.1