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

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pradeepiisc/
bert-base-uncased-issues-128

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google-bert/bert-base-uncased

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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: 1.1665

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
2.1115	1.0	291	1.6910
1.6344	2.0	582	1.3645
1.4807	3.0	873	1.4238
1.3931	4.0	1164	1.4296
1.3413	5.0	1455	1.2654
1.2873	6.0	1746	1.3083
1.2302	7.0	2037	1.2093
1.2123	8.0	2328	1.2651
1.179	9.0	2619	1.2634
1.148	10.0	2910	1.2130
1.127	11.0	3201	1.2644
1.0993	12.0	3492	1.1545
1.0964	13.0	3783	1.1527
1.079	14.0	4074	1.0715
1.0662	15.0	4365	1.2462
1.067	16.0	4656	1.1665

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3