bert-base-uncased

This model was trained on a dataset of issues from github. It achieves the following results on the evaluation set:

• Loss: 1.2437

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

Masked language model trained on github issue data with token length of 128.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 1
• 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
2.205	1.0	9303	1.7893
1.8417	2.0	18606	1.7270
1.7103	3.0	27909	1.6650
1.6014	4.0	37212	1.6052
1.523	5.0	46515	1.5782
1.4588	6.0	55818	1.4836
1.3922	7.0	65121	1.4289
1.317	8.0	74424	1.4414
1.2622	9.0	83727	1.4322
1.2123	10.0	93030	1.3651
1.1753	11.0	102333	1.3636
1.1164	12.0	111636	1.2872
1.0636	13.0	120939	1.3705
1.021	14.0	130242	1.3013
0.996	15.0	139545	1.2756
0.9625	16.0	148848	1.2437

Framework versions

• Transformers 4.14.1
• Pytorch 1.9.0
• Datasets 1.11.0
• Tokenizers 0.10.3