mobilebert_add_GLUE_Experiment_logit_kd_qqp – AI Model by gokuls | AlphaNeural AI

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gokuls/
mobilebert_add_GLUE_Experiment_logit_kd_qqp

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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mobilebert_add_GLUE_Experiment_logit_kd_qqp

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: 0.8079
Accuracy: 0.7570
F1: 0.6049
Combined Score: 0.6810

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
1.2837	1.0	2843	1.2201	0.6318	0.0	0.3159
1.076	2.0	5686	0.8477	0.7443	0.5855	0.6649
0.866	3.0	8529	0.8217	0.7518	0.5924	0.6721
0.8317	4.0	11372	0.8136	0.7565	0.6243	0.6904
0.8122	5.0	14215	0.8126	0.7588	0.6352	0.6970
0.799	6.0	17058	0.8079	0.7570	0.6049	0.6810
386581134871678353408.0000	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
0.0	11.0	31273	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