mobilebert_add_GLUE_Experiment_logit_kd_qqp_256

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

• Loss: 0.8027
• Accuracy: 0.7596
• F1: 0.6364
• Combined Score: 0.6980

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	F1	Combined Score
1.2838	1.0	2843	1.2200	0.6318	0.0	0.3159
1.0184	2.0	5686	0.8422	0.7473	0.5924	0.6698
0.8633	3.0	8529	0.8232	0.7520	0.5963	0.6742
0.834	4.0	11372	0.8193	0.7563	0.6271	0.6917
0.812	5.0	14215	0.8027	0.7596	0.6364	0.6980
0.7871	6.0	17058	nan	0.6318	0.0	0.3159
0.0	7.0	19901	nan	0.6318	0.0	0.3159
0.0	8.0	22744	nan	0.6318	0.0	0.3159
0.0	9.0	25587	nan	0.6318	0.0	0.3159
0.0	10.0	28430	nan	0.6318	0.0	0.3159

Framework versions

• Transformers 4.26.0
• Pytorch 1.14.0a0+410ce96
• Datasets 2.9.0
• Tokenizers 0.13.2