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mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc

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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - f1
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+ model-index:
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+ - name: mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc
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+
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+ This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1274
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+ - Accuracy: 0.9902
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+ - F1: 0.9929
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+ - Combined Score: 0.9915
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 128
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+ - eval_batch_size: 128
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+ - seed: 10
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+ - distributed_type: multi-GPU
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
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+ | 0.2964 | 1.0 | 1959 | 0.2026 | 0.9608 | 0.9718 | 0.9663 |
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+ | 0.2307 | 2.0 | 3918 | 0.1943 | 0.9706 | 0.9789 | 0.9748 |
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+ | 0.2221 | 3.0 | 5877 | 0.1874 | 0.9804 | 0.9858 | 0.9831 |
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+ | 0.2163 | 4.0 | 7836 | 0.1703 | 0.9853 | 0.9894 | 0.9873 |
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+ | 0.2115 | 5.0 | 9795 | 0.1805 | 0.9853 | 0.9894 | 0.9873 |
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+ | 0.2071 | 6.0 | 11754 | 0.1682 | 0.9804 | 0.9859 | 0.9831 |
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+ | 0.2036 | 7.0 | 13713 | 0.1583 | 0.9877 | 0.9911 | 0.9894 |
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+ | 0.2007 | 8.0 | 15672 | 0.1628 | 0.9926 | 0.9947 | 0.9936 |
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+ | 0.1985 | 9.0 | 17631 | 0.1548 | 0.9853 | 0.9894 | 0.9873 |
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+ | 0.1965 | 10.0 | 19590 | 0.1583 | 0.9877 | 0.9911 | 0.9894 |
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+ | 0.195 | 11.0 | 21549 | 0.1527 | 0.9902 | 0.9928 | 0.9915 |
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+ | 0.1938 | 12.0 | 23508 | 0.1512 | 0.9902 | 0.9929 | 0.9915 |
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+ | 0.1926 | 13.0 | 25467 | 0.1426 | 0.9951 | 0.9964 | 0.9958 |
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+ | 0.1917 | 14.0 | 27426 | 0.1436 | 0.9951 | 0.9964 | 0.9958 |
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+ | 0.191 | 15.0 | 29385 | 0.1503 | 0.9926 | 0.9946 | 0.9936 |
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+ | 0.1901 | 16.0 | 31344 | 0.1461 | 0.9951 | 0.9964 | 0.9958 |
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+ | 0.1894 | 17.0 | 33303 | 0.1498 | 0.9975 | 0.9982 | 0.9979 |
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+ | 0.1888 | 18.0 | 35262 | 0.1402 | 0.9902 | 0.9929 | 0.9915 |
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+ | 0.1882 | 19.0 | 37221 | 0.1420 | 0.9926 | 0.9946 | 0.9936 |
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+ | 0.1876 | 20.0 | 39180 | 0.1346 | 0.9902 | 0.9929 | 0.9915 |
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+ | 0.1871 | 21.0 | 41139 | 0.1396 | 0.9951 | 0.9964 | 0.9958 |
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+ | 0.1867 | 22.0 | 43098 | 0.1443 | 0.9951 | 0.9964 | 0.9958 |
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+ | 0.1862 | 23.0 | 45057 | 0.1346 | 0.9926 | 0.9947 | 0.9936 |
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+ | 0.1857 | 24.0 | 47016 | 0.1361 | 0.9951 | 0.9964 | 0.9958 |
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+ | 0.1854 | 25.0 | 48975 | 0.1318 | 0.9926 | 0.9947 | 0.9936 |
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+ | 0.185 | 26.0 | 50934 | 0.1310 | 0.9902 | 0.9929 | 0.9915 |
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+ | 0.1846 | 27.0 | 52893 | 0.1302 | 0.9926 | 0.9947 | 0.9936 |
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+ | 0.1842 | 28.0 | 54852 | 0.1329 | 0.9951 | 0.9964 | 0.9958 |
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+ | 0.1839 | 29.0 | 56811 | 0.1300 | 0.9902 | 0.9929 | 0.9915 |
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+ | 0.1836 | 30.0 | 58770 | 0.1328 | 0.9902 | 0.9929 | 0.9915 |
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+ | 0.1832 | 31.0 | 60729 | 0.1327 | 0.9902 | 0.9929 | 0.9915 |
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+ | 0.1829 | 32.0 | 62688 | 0.1308 | 0.9902 | 0.9929 | 0.9915 |
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+ | 0.1826 | 33.0 | 64647 | 0.1287 | 0.9902 | 0.9929 | 0.9915 |
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+ | 0.1824 | 34.0 | 66606 | 0.1309 | 0.9926 | 0.9947 | 0.9936 |
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+ | 0.1821 | 35.0 | 68565 | 0.1309 | 0.9926 | 0.9947 | 0.9936 |
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+ | 0.1818 | 36.0 | 70524 | 0.1271 | 0.9902 | 0.9929 | 0.9915 |
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+ | 0.1816 | 37.0 | 72483 | 0.1278 | 0.9877 | 0.9911 | 0.9894 |
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+ | 0.1813 | 38.0 | 74442 | 0.1280 | 0.9902 | 0.9929 | 0.9915 |
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+ | 0.1811 | 39.0 | 76401 | 0.1289 | 0.9902 | 0.9929 | 0.9915 |
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+ | 0.1809 | 40.0 | 78360 | 0.1290 | 0.9877 | 0.9911 | 0.9894 |
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+ | 0.1807 | 41.0 | 80319 | 0.1256 | 0.9877 | 0.9911 | 0.9894 |
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+ | 0.1805 | 42.0 | 82278 | 0.1268 | 0.9926 | 0.9947 | 0.9936 |
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+ | 0.1803 | 43.0 | 84237 | 0.1274 | 0.9926 | 0.9947 | 0.9936 |
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+ | 0.1801 | 44.0 | 86196 | 0.1277 | 0.9926 | 0.9947 | 0.9936 |
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+ | 0.1799 | 45.0 | 88155 | 0.1264 | 0.9926 | 0.9947 | 0.9936 |
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+ | 0.1797 | 46.0 | 90114 | 0.1274 | 0.9902 | 0.9929 | 0.9915 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.0
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+ - Pytorch 1.14.0a0+410ce96
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+ - Datasets 2.9.0
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+ - Tokenizers 0.13.2