mobilebert_sa_GLUE_Experiment_mnli_256

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

• Loss: 0.8790
• Accuracy: 0.6030

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
1.0008	1.0	3068	0.9490	0.5405
0.9205	2.0	6136	0.9166	0.5675
0.8928	3.0	9204	0.9022	0.5786
0.872	4.0	12272	0.8843	0.5967
0.8531	5.0	15340	0.8807	0.5959
0.8359	6.0	18408	0.8763	0.5999
0.8197	7.0	21476	0.8815	0.6009
0.8028	8.0	24544	0.9012	0.5934
0.786	9.0	27612	0.8633	0.6191
0.769	10.0	30680	0.8734	0.6098
0.752	11.0	33748	0.8682	0.6220
0.736	12.0	36816	0.8741	0.6175
0.7204	13.0	39884	0.8994	0.6048
0.7038	14.0	42952	0.8940	0.6079

Framework versions

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