mobilebert_add_GLUE_Experiment_wnli_128

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

• Loss: 0.6908
• 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: 5e-05
• train_batch_size: 128
• eval_batch_size: 128
• seed: 10
• distributed_type: multi-GPU
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6936	1.0	5	0.6912	0.5634
0.6932	2.0	10	0.6918	0.5634
0.6931	3.0	15	0.6920	0.5634
0.693	4.0	20	0.6916	0.5634
0.693	5.0	25	0.6912	0.5634
0.693	6.0	30	0.6911	0.5634
0.693	7.0	35	0.6908	0.5634
0.693	8.0	40	0.6911	0.5634
0.6931	9.0	45	0.6908	0.5634
0.693	10.0	50	0.6911	0.5634
0.693	11.0	55	0.6916	0.5634
0.693	12.0	60	0.6916	0.5634
0.693	13.0	65	0.6917	0.5634
0.6929	14.0	70	0.6918	0.5634

Framework versions

• Transformers 4.26.0
• Pytorch 1.14.0a0+410ce96
• Datasets 2.8.0
• Tokenizers 0.13.2