Modelpublic

gokuls/mobilebert_sa_GLUE_Experiment_logit_kd_mrpc

sourceHugging Faceapache-2.0updated 4y agoView on Hugging Face

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Model Card

mobilebertsaGLUEExperimentlogitkdmrpc

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

—Loss: 0.5133
—Accuracy: 0.6740
—F1: 0.7772
—Combined Score: 0.7256

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
—trainbatchsize: 128
—evalbatchsize: 128
—seed: 10
—distributed_type: multi-GPU
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Combined Score
0.6228	1.0	29	0.5556	0.6838	0.8122	0.7480
0.611	2.0	58	0.5551	0.6838	0.8122	0.7480
0.6095	3.0	87	0.5538	0.6838	0.8122	0.7480
0.6062	4.0	116	0.5503	0.6838	0.8122	0.7480
0.5825	5.0	145	0.5262	0.6985	0.8167	0.7576
0.4981	6.0	174	0.5197	0.6936	0.8038	0.7487
0.468	7.0	203	0.5133	0.6740	0.7772	0.7256
0.3901	8.0	232	0.5382	0.6838	0.7757	0.7297
0.323	9.0	261	0.6140	0.6789	0.7657	0.7223
0.2674	10.0	290	0.5512	0.6740	0.7687	0.7214
0.2396	11.0	319	0.6467	0.6667	0.7631	0.7149
0.2127	12.0	348	0.7811	0.6716	0.7690	0.7203

Framework versions

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