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: 1.1922

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 OptimizerNames.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
2.1169	1.0	292	1.6771
1.6363	2.0	584	1.4808
1.4818	3.0	876	1.4376
1.3859	4.0	1168	1.3753
1.339	5.0	1460	1.2945
1.283	6.0	1752	1.2843
1.2383	7.0	2044	1.1759
1.2099	8.0	2336	1.3379
1.1649	9.0	2628	1.1895
1.1578	10.0	2920	1.1954
1.1257	11.0	3212	1.1181
1.1047	12.0	3504	1.2260
1.1003	13.0	3796	1.0715
1.0793	14.0	4088	1.1815
1.0732	15.0	4380	1.1907
1.0489	16.0	4672	1.1922

Framework versions

• Transformers 4.47.0
• Pytorch 2.5.1
• Datasets 3.2.0
• Tokenizers 0.21.0