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

You can deploy this model and start earning money today!

cvnberk/
bert-base-uncased-issues-128

like

0

generated_from_trainer

google-bert/bert-base-uncased

endpoints_compatible

Views

No views yet

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: 1.2137

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
2.0966	1.0	291	1.6190
1.6197	2.0	582	1.5317
1.485	3.0	873	1.4164
1.3992	4.0	1164	1.4064
1.3219	5.0	1455	1.3900
1.2851	6.0	1746	1.2096
1.2328	7.0	2037	1.3019
1.2113	8.0	2328	1.2779
1.1674	9.0	2619	1.2312
1.1443	10.0	2910	1.1830
1.1171	11.0	3201	1.1692
1.1067	12.0	3492	1.2364
1.0846	13.0	3783	1.1871
1.0815	14.0	4074	1.1354
1.054	15.0	4365	1.1771
1.0565	16.0	4656	1.2137

Framework versions

Transformers 4.32.1
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3