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

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tanviraumi/
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: 1.2337

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: 128
eval_batch_size: 32
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
2.3389	1.0	73	1.7400
1.8014	2.0	146	1.4690
1.634	3.0	219	1.4783
1.5461	4.0	292	1.3912
1.4706	5.0	365	1.3109
1.4161	6.0	438	1.3405
1.3664	7.0	511	1.3459
1.332	8.0	584	1.2745
1.3029	9.0	657	1.2633
1.2871	10.0	730	1.2336
1.2807	11.0	803	1.2966
1.2569	12.0	876	1.1508
1.2392	13.0	949	1.2530
1.237	14.0	1022	1.2485
1.2169	15.0	1095	1.2592
1.2272	16.0	1168	1.2337

Framework versions

Transformers 4.19.1
Pytorch 1.12.0.dev20220513+cu113
Datasets 2.2.1
Tokenizers 0.12.1