bert-base-uncased-issues-128 – AI Model by takao3548 | AlphaNeural AI

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takao3548/
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: 1.2751

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 16

Training results

Training Loss	Epoch	Step	Validation Loss
2.3494	1.0	291	1.8032
1.7514	2.0	582	1.5877
1.587	3.0	873	1.4322
1.4774	4.0	1164	1.4187
1.4037	5.0	1455	1.2945
1.3534	6.0	1746	1.4275
1.2994	7.0	2037	1.3524
1.2719	8.0	2328	1.3865
1.2286	9.0	2619	1.2797
1.2039	10.0	2910	1.2218
1.1924	11.0	3201	1.1750
1.1774	12.0	3492	1.2321
1.1526	13.0	3783	1.2489
1.1409	14.0	4074	1.2568
1.1367	15.0	4365	1.2646
1.1273	16.0	4656	1.2751

Framework versions

Transformers 4.50.0.dev0
Pytorch 2.6.0+cu124
Datasets 3.3.2
Tokenizers 0.21.0