gokuls / mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_128

huggingface.co
Total runs: 19
24-hour runs: 0
7-day runs: 0
30-day runs: 6
Model's Last Updated: February 03 2023
text-classification

Introduction of mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_128

Model Details of mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_128

mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_128

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: 0.1262
  • Accuracy: 0.9877
  • F1: 0.9911
  • Combined Score: 0.9894
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
0.3021 1.0 1959 0.2407 0.9510 0.9636 0.9573
0.2326 2.0 3918 0.2009 0.9779 0.9841 0.9810
0.224 3.0 5877 0.1790 0.9730 0.9807 0.9769
0.219 4.0 7836 0.1789 0.9804 0.9859 0.9831
0.2153 5.0 9795 0.1804 0.9804 0.9859 0.9831
0.2121 6.0 11754 0.1754 0.9755 0.9824 0.9789
0.2088 7.0 13713 0.1661 0.9804 0.9859 0.9831
0.2056 8.0 15672 0.1654 0.9779 0.9841 0.9810
0.2031 9.0 17631 0.1714 0.9828 0.9876 0.9852
0.2012 10.0 19590 0.1617 0.9828 0.9876 0.9852
0.1993 11.0 21549 0.1610 0.9828 0.9876 0.9852
0.1978 12.0 23508 0.1507 0.9853 0.9894 0.9873
0.1964 13.0 25467 0.1496 0.9902 0.9929 0.9915
0.1953 14.0 27426 0.1569 0.9828 0.9876 0.9852
0.1943 15.0 29385 0.1524 0.9877 0.9911 0.9894
0.1934 16.0 31344 0.1492 0.9877 0.9911 0.9894
0.1926 17.0 33303 0.1480 0.9902 0.9929 0.9915
0.1918 18.0 35262 0.1416 0.9828 0.9876 0.9852
0.1912 19.0 37221 0.1420 0.9853 0.9894 0.9873
0.1905 20.0 39180 0.1396 0.9853 0.9894 0.9873
0.1899 21.0 41139 0.1458 0.9853 0.9894 0.9873
0.1893 22.0 43098 0.1484 0.9877 0.9911 0.9894
0.1888 23.0 45057 0.1407 0.9877 0.9911 0.9894
0.1883 24.0 47016 0.1372 0.9804 0.9858 0.9831
0.1878 25.0 48975 0.1354 0.9877 0.9911 0.9894
0.1873 26.0 50934 0.1368 0.9902 0.9929 0.9915
0.1869 27.0 52893 0.1378 0.9926 0.9947 0.9936
0.1865 28.0 54852 0.1381 0.9853 0.9894 0.9873
0.1861 29.0 56811 0.1329 0.9877 0.9911 0.9894
0.1857 30.0 58770 0.1342 0.9902 0.9929 0.9915
0.1854 31.0 60729 0.1346 0.9902 0.9929 0.9915
0.1849 32.0 62688 0.1323 0.9902 0.9929 0.9915
0.1846 33.0 64647 0.1317 0.9877 0.9911 0.9894
0.1843 34.0 66606 0.1318 0.9877 0.9911 0.9894
0.1839 35.0 68565 0.1311 0.9926 0.9947 0.9936
0.1837 36.0 70524 0.1291 0.9877 0.9911 0.9894
0.1834 37.0 72483 0.1313 0.9853 0.9893 0.9873
0.1831 38.0 74442 0.1262 0.9877 0.9911 0.9894
0.1828 39.0 76401 0.1288 0.9877 0.9911 0.9894
0.1825 40.0 78360 0.1295 0.9926 0.9947 0.9936
0.1823 41.0 80319 0.1277 0.9902 0.9929 0.9915
0.182 42.0 82278 0.1265 0.9902 0.9929 0.9915
0.1818 43.0 84237 0.1273 0.9902 0.9929 0.9915
Framework versions
  • Transformers 4.26.0
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.9.0
  • Tokenizers 0.13.2

Runs of gokuls mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_128 on huggingface.co

19
Total runs
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24-hour runs
4
3-day runs
0
7-day runs
6
30-day runs

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