bert_base_lda_5_wnli

This model is a fine-tuned version of gokulsrinivasagan/bert_base_lda_5 on the GLUE WNLI dataset. It achieves the following results on the evaluation set:

• Loss: 0.6849
• Accuracy: 0.5634

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: 0.001
• train_batch_size: 256
• eval_batch_size: 256
• seed: 10
• 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: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.121	1.0	3	0.8205	0.5634
1.6034	2.0	6	1.7293	0.4366
0.9483	3.0	9	0.7649	0.4366
0.7514	4.0	12	0.7557	0.5634
0.746	5.0	15	0.8105	0.4366
0.7896	6.0	18	0.7383	0.4366
0.7573	7.0	21	0.6853	0.5634
0.6951	8.0	24	0.8346	0.4366
0.746	9.0	27	0.6906	0.5634
0.6992	10.0	30	0.6849	0.5634
0.6942	11.0	33	0.7009	0.4366
0.7	12.0	36	0.6951	0.4366
0.6976	13.0	39	0.6854	0.5634
0.6999	14.0	42	0.6901	0.5634
0.6948	15.0	45	0.6926	0.5634

Framework versions

• Transformers 4.46.3
• Pytorch 2.2.1+cu118
• Datasets 2.17.0
• Tokenizers 0.20.3