bert-base-uncased-issues-128 – AI Model by betelgeux | 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: 2.0348

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
2.3932	1.0	1409	2.0750
2.1659	2.0	2818	1.9781
2.0364	3.0	4227	2.1215
1.9399	4.0	5636	2.1018
1.8857	5.0	7045	1.9919
1.813	6.0	8454	2.2653
1.7505	7.0	9863	2.0857
1.7196	8.0	11272	1.9211
1.672	9.0	12681	1.9853
1.6379	10.0	14090	2.0391
1.6037	11.0	15499	1.9305
1.5699	12.0	16908	2.0291
1.5363	13.0	18317	2.0492
1.5155	14.0	19726	1.8807
1.4999	15.0	21135	1.8604
1.4784	16.0	22544	2.0348

Framework versions

Transformers 4.18.0
Pytorch 1.12.1
Datasets 2.4.0
Tokenizers 0.12.1